Reconfiguration planning is recognized as an important factor for reducing the cost of manufacturing reconfigurable products, and the associated main task is to generate a set of optimal or near-optimal reconfiguratio...Reconfiguration planning is recognized as an important factor for reducing the cost of manufacturing reconfigurable products, and the associated main task is to generate a set of optimal or near-optimal reconfiguration sequences using some effect algorithms. A method is developed to generate a Petri net as the reconfiguration tree to represent two-state-transit of product, which solved the representation problem of reconfiguring interfaces replacement. Relating with this method, two heuristic algorithms are proposed to generate task sequences which considering economics to search reconfiguration paths effectively. At last, an objective evaluation is applied to compare these two heuristic algorithms to other ones. The developed reconfiguration task planning heuristic algorithms can generate better strategies and plans for reconfiguration. The research finds are exemplified with struts reconfiguration of reconfigurable parallel kinematics machine （RPKM）.展开更多
Heuristic optimization algorithms have been widely used in solving complex optimization problems in various fields such as engineering,economics,and computer science.These algorithms are designed to find high-quality ...Heuristic optimization algorithms have been widely used in solving complex optimization problems in various fields such as engineering,economics,and computer science.These algorithms are designed to find high-quality solutions efficiently by balancing exploration of the search space and exploitation of promising solutions.While heuristic optimization algorithms vary in their specific details,they often exhibit common patterns that are essential to their effectiveness.This paper aims to analyze and explore common patterns in heuristic optimization algorithms.Through a comprehensive review of the literature,we identify the patterns that are commonly observed in these algorithms,including initialization,local search,diversity maintenance,adaptation,and stochasticity.For each pattern,we describe the motivation behind it,its implementation,and its impact on the search process.To demonstrate the utility of our analysis,we identify these patterns in multiple heuristic optimization algorithms.For each case study,we analyze how the patterns are implemented in the algorithm and how they contribute to its performance.Through these case studies,we show how our analysis can be used to understand the behavior of heuristic optimization algorithms and guide the design of new algorithms.Our analysis reveals that patterns in heuristic optimization algorithms are essential to their effectiveness.By understanding and incorporating these patterns into the design of new algorithms,researchers can develop more efficient and effective optimization algorithms.展开更多
Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm opt...Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm optimization （HPSO） algorithm is proposed to solve the decision-making （DM） problem. HA facilitates to search the local optimum in the neighborhood of a solution, while the PSO algorithm tends to explore the search space for possible solutions. Combining the advantages of HA and PSO, HPSO algorithms can find out the global optimum quickly and efficiently. It obtains the DM solution by seeking for the optimal assignment of missiles of friendly fighter aircrafts （FAs） to hostile FAs. Simulation results show that the proposed algorithm is superior to the general PSO algorithm and two GA based algorithms in searching for the best solution to the DM problem.展开更多
In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms...In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms to solve the problem of multi-UAV path planning.The Dung Beetle Optimization(DBO)algorithm has been widely applied due to its diverse search patterns in the above algorithms.However,the update strategies for the rolling and thieving dung beetles of the DBO algorithm are overly simplistic,potentially leading to an inability to fully explore the search space and a tendency to converge to local optima,thereby not guaranteeing the discovery of the optimal path.To address these issues,we propose an improved DBO algorithm guided by the Landmark Operator(LODBO).Specifically,we first use tent mapping to update the population strategy,which enables the algorithm to generate initial solutions with enhanced diversity within the search space.Second,we expand the search range of the rolling ball dung beetle by using the landmark factor.Finally,by using the adaptive factor that changes with the number of iterations.,we improve the global search ability of the stealing dung beetle,making it more likely to escape from local optima.To verify the effectiveness of the proposed method,extensive simulation experiments are conducted,and the result shows that the LODBO algorithm can obtain the optimal path using the shortest time compared with the Genetic Algorithm(GA),the Gray Wolf Optimizer(GWO),the Whale Optimization Algorithm(WOA)and the original DBO algorithm in the disaster search and rescue task set.展开更多
Lot scheduling problem with idle time transfer between processes to minimize mean flow time is very important because to minimize mean flow time is to minimize work in process. But the problem is NP hard and no polyn...Lot scheduling problem with idle time transfer between processes to minimize mean flow time is very important because to minimize mean flow time is to minimize work in process. But the problem is NP hard and no polynomial algorithm exists to guarantee optimal solution. Based the analysis the mathematical structure of the problem, the paper presents a new heuristic algorithm. Computer simulation shows that the proposed heuristic algorithm performs well in terms of both quality of solution and execution speed.展开更多
Recently, the development of Industrial Internet of Things hastaken the advantage of 5G network to be more powerful and more intelligent.However, the upgrading of 5G network will cause a variety of issues increase,one...Recently, the development of Industrial Internet of Things hastaken the advantage of 5G network to be more powerful and more intelligent.However, the upgrading of 5G network will cause a variety of issues increase,one of them is the increased cost of coverage. In this paper, we proposea sustainable wireless sensor networks system, which avoids the problemsbrought by 5G network system to some extent. In this system, deployingrelays and selecting routing are for the sake of communication and charging.The main aim is to minimize the total energy-cost of communication underthe precondition, where each terminal with low-power should be charged byat least one relay. Furthermore, from the perspective of graph theory, weextract a combinatorial optimization problem from this system. After that,as to four different cases, there are corresponding different versions of theproblem. We give the proofs of computational complexity for these problems,and two heuristic algorithms for one of them are proposed. Finally, theextensive experiments compare and demonstrate the performances of thesetwo algorithms.展开更多
Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generat...Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generated control overhead consists of controller-device and inter-controller communications to discover the network topology, exchange configurations, and set up and modify flow tables in the control plane. However, due to the high complexity of the proposed optimization model to the CPP, heuristic algorithms have been reported to find near-optimal solutions faster for large-scale wired networks. In this paper, the objective is to extend those existing heuristic algorithms to solve a proposed optimization model to the CPP in software-<span>defined multihop wireless networking</span><span> (SDMWN).</span>Our results demonstrate that using ranking degrees assigned to the possible controller placements, including the average distance to other devices as a degree or the connectivity degree of each placement, the extended heuristic algorithms are able to achieve the optimal solution in small-scale networks in terms of the generated control overhead and the number of controllers selected in the network. As a result, using extended heuristic algorithms, the average number of hops among devices and their assigned controllers as well as among controllers will be reduced. Moreover, these algorithms are able tolower<span "=""> </span>the control overhead in large-scale networks and select fewer controllers compared to an extended algorithm that solves the CPP in SDMWN based on a randomly selected controller placement approach.展开更多
Resource-constrained project scheduling problem（RCPSP） is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities＇ cost with the re...Resource-constrained project scheduling problem（RCPSP） is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities＇ cost with the resource constraints that is a critical sub-problem in partner selection of construction supply chain management because the capacities of the renewable resources supplied by the partners will effect on the project scheduling. Its mathematic model is presented firstly, and analysis on the characteristic of the problem shows that the objective function is non-regular and the problem is NP-complete following which the basic idea for solution is clarified. Based on a definition of preposing activity cost matrix, a heuristic algorithm is brought forward. Analyses on the complexity of the heuristics and the result of numerical studies show that the heuristic algorithm is feasible and relatively effective.展开更多
We present a new algorithm for nesting problems.Many equally spaced points are set on a sheet,and a piece is moved to one of the points and rotated by an angle.Both the point and the rotation angle constitute the pack...We present a new algorithm for nesting problems.Many equally spaced points are set on a sheet,and a piece is moved to one of the points and rotated by an angle.Both the point and the rotation angle constitute the packing attitude of the piece.We propose a new algorithm named HAPE(Heuristic Algorithm based on the principle of minimum total Potential Energy) to find the optimal packing attitude at which the piece has the lowest center of gravity.In addition,a new technique for polygon overlap testing is proposed which avoids the time-consuming calculation of no-fit-polygon(NFP).The detailed implementation of HAPE is presented and two computational experiments are described.The first experiment is based on a real industrial problem and the second on 11 published benchmark problems.Using a hill-climbing(HC) search method,the proposed algorithm performs well in comparison with other published solutions.展开更多
An optimal layout or three-dimensional spatial distribution of stopes guarantees the maximum profitability over life span of an underground mining operation.Thus,stope optimization is one of the key areas in undergrou...An optimal layout or three-dimensional spatial distribution of stopes guarantees the maximum profitability over life span of an underground mining operation.Thus,stope optimization is one of the key areas in underground mine planning practice.However,the computational complexity in developing an optimal stope layout has been a reason for limited availability of the algorithms offering solution to this problem.This article shares a new and efficient heuristic algorithm that considers a three-dimensional ore body model as an input,maximizes the economic value,and satisfies the physical mining and geotechnical constraints for generating an optimal stope layout.An implementation at a copper deposit demonstrates the applicability and robustness of the algorithm.A parallel processing based modification improving the performance of the original algorithm in terms of enormous computational time saving is also presented.展开更多
A new heuristic algorithm is proposed for solving general integer linear programming problems. In the algorithm, the objective function hyperplane is used as a cutting plane, and then by introducing a special set of a...A new heuristic algorithm is proposed for solving general integer linear programming problems. In the algorithm, the objective function hyperplane is used as a cutting plane, and then by introducing a special set of assistant sets, an efficient heuristic search for the solution to the integer linear program is carried out in the sets on the objective function hyperplane. A simple numerical example shows that the algorithm is efficient for some problems, and therefore, of practical interest.展开更多
E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking d...E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.展开更多
We report an overlapping sampling scheme to accelerate computational ghost imaging for imaging moving targets,based on reordering a set of Hadamard modulation matrices by means of a heuristic algorithm. The new conden...We report an overlapping sampling scheme to accelerate computational ghost imaging for imaging moving targets,based on reordering a set of Hadamard modulation matrices by means of a heuristic algorithm. The new condensed overlapped matrices are then designed to shorten and optimize encoding of the overlapped patterns, which are shown to be much superior to the random matrices. In addition, we apply deep learning to image the target, and use the signal acquired by the bucket detector and corresponding real image to train the neural network. Detailed comparisons show that our new method can improve the imaging speed by as much as an order of magnitude, and improve the image quality as well.展开更多
The execution process of satellite-ground clock synchronization and ephemeris uploading in the system is analyzed,as well as their characterized operation and their relationship.Based on the analysis of the scheduling...The execution process of satellite-ground clock synchronization and ephemeris uploading in the system is analyzed,as well as their characterized operation and their relationship.Based on the analysis of the scheduling goal and constraint character,a heuristics rule-based multi-stage link scheduling algorithm was put forward.The algorithm distinguishes the on-off-frontier satellites from the others and schedules them by turns.The paper presented the main flow as well as the detailed design of the rule.Finally based on the current COMPASS global system,some typical resources and constraints are selected to generate an instance.Then the comparison analysis between the heuristics scheduling algorithm and three other traditional scheduling strategies are carried out.The result shows the validity and reasonability of the multi-stage strategy.展开更多
This paper investigates traffic flow of connected and automated vehicles at lane drop on two-lane highway. We evaluate and compare performance of an optimization-based control algorithm(OCA) with that of a heuristic r...This paper investigates traffic flow of connected and automated vehicles at lane drop on two-lane highway. We evaluate and compare performance of an optimization-based control algorithm(OCA) with that of a heuristic rules-based algorithm(HRA). In the OCA, the average speed of each vehicle is maximized. In the HRA, virtual vehicle and restriction of the command acceleration caused by the virtual vehicle are introduced. It is found that(i) capacity under the HRA(denoted as C_(H)) is smaller than capacity under the OCA;(ii) the travel delay is always smaller under the OCA, but driving is always much more comfortable under the HRA;(iii) when the inflow rate is smaller than C_(H), the HRA outperforms the OCA with respect to the fuel consumption and the monetary cost;(iv) when the inflow rate is larger than C_(H), the HRA initially performs better with respect to the fuel consumption and the monetary cost, but the OCA would become better after certain time. The spatiotemporal pattern and speed profile of traffic flow are presented, which explains the reason underlying the different performance. The study is expected to help for better understanding of the two different types of algorithm.展开更多
This paper presents the two-machine flowshop group scheduling problem with the optimal objective of maximum lateness. A dominance rule within group and a dominance rule between groups are established. These dominance ...This paper presents the two-machine flowshop group scheduling problem with the optimal objective of maximum lateness. A dominance rule within group and a dominance rule between groups are established. These dominance rules along with a previously established dominance rule are used to develop a heuristic algorithm. Experimental results are given and analyzed.展开更多
To guarantee the optimal reduct set, a heuristic reduction algorithm is proposed, which considers the distinguishing information between the members of each pair decision classes. Firstly the pairwise positive region ...To guarantee the optimal reduct set, a heuristic reduction algorithm is proposed, which considers the distinguishing information between the members of each pair decision classes. Firstly the pairwise positive region is defined, based on which the pairwise significance measure is calculated between the members of each pair classes. Finally the weighted pairwise significance of attribute is used as the attribute reduction criterion, which indicates the necessity of attributes very well. By introducing the noise tolerance factor, the new algorithm can tolerate noise to some extent. Experimental results show the advantages of our novel heuristic reduction algorithm over the traditional attribute dependency based algorithm.展开更多
Based on a presented inference algorithm of fuzzy reasoning, a fuzzy reasoning system is made up. A method of modeling the fuzzy reasoning system, and the setting up of the reasoning knowledge based and reasoning rule...Based on a presented inference algorithm of fuzzy reasoning, a fuzzy reasoning system is made up. A method of modeling the fuzzy reasoning system, and the setting up of the reasoning knowledge based and reasoning rules are studied in this paper. Then a heuristic inference algorithm is presented according to the system.展开更多
This framework proposes a heuristic algorithm based on LP （linear programming） for optimizing the electricity cost in large residential buildings, in a smart grid environment. Our heuristic tackles large multi-objec...This framework proposes a heuristic algorithm based on LP （linear programming） for optimizing the electricity cost in large residential buildings, in a smart grid environment. Our heuristic tackles large multi-objective energy allocation problem （large number of appliances and high time resolution）. The primary goal is to reduce the electricity bills, and discomfort factor. Also, increase the utilization of domestic renewable energy, and reduce the running time of the optimization algorithm. Our heuristic algorithm uses linear programming relaxation, and two rounding strategies. The first technique, called CR （cumulative rounding）, is designed for thermostatic appliances such as air conditioners and electric heaters, and the second approach, called MCR （minimum cost rounding）, is designed for other interruptible appliances. The results show that the proposed heuristic algorithm can be used to solve large MILP （mixed integer linear programming） problems and gives a decent suboptimal solution in polynomial time.展开更多
The communication resources scheduling problem of the satellite network contains the user-satellite association problem,the user-beam matching problem,and the beam power allocation problem.Different optimization probl...The communication resources scheduling problem of the satellite network contains the user-satellite association problem,the user-beam matching problem,and the beam power allocation problem.Different optimization problems contain different types of variables.Mult-type variables and three coupling problems cause the cooperative scheduling problem to be complex.In this paper,we propose a mixed vector encoding heuristic algorithm(MVEHA)to optimize the joint resources allocation problem of the multiple beams satellite network.Specifically,we use the 0-1 encoding vector to represent the user-satellite association scheme,the user-beam matching scheme is denoted by the continuous vector with priority,and a normalization vector is designed to encoded the beam power allocation scheme.Due to the mixed vector encoding method,we design two optimization operators to guide the search direction of the population.Compared to the conventional optimization algorithm,the simulation experiment shows MVEHA has better solution performance and robustness to solve the communication resources allocation problem of the satellite network.展开更多
基金Supported by the High Technology Research and Development Programme of China （No. 2006AA04Z133） and the National Natural Science Foundation of China （No. 50605035, 50510488）.
文摘Reconfiguration planning is recognized as an important factor for reducing the cost of manufacturing reconfigurable products, and the associated main task is to generate a set of optimal or near-optimal reconfiguration sequences using some effect algorithms. A method is developed to generate a Petri net as the reconfiguration tree to represent two-state-transit of product, which solved the representation problem of reconfiguring interfaces replacement. Relating with this method, two heuristic algorithms are proposed to generate task sequences which considering economics to search reconfiguration paths effectively. At last, an objective evaluation is applied to compare these two heuristic algorithms to other ones. The developed reconfiguration task planning heuristic algorithms can generate better strategies and plans for reconfiguration. The research finds are exemplified with struts reconfiguration of reconfigurable parallel kinematics machine （RPKM）.
文摘Heuristic optimization algorithms have been widely used in solving complex optimization problems in various fields such as engineering,economics,and computer science.These algorithms are designed to find high-quality solutions efficiently by balancing exploration of the search space and exploitation of promising solutions.While heuristic optimization algorithms vary in their specific details,they often exhibit common patterns that are essential to their effectiveness.This paper aims to analyze and explore common patterns in heuristic optimization algorithms.Through a comprehensive review of the literature,we identify the patterns that are commonly observed in these algorithms,including initialization,local search,diversity maintenance,adaptation,and stochasticity.For each pattern,we describe the motivation behind it,its implementation,and its impact on the search process.To demonstrate the utility of our analysis,we identify these patterns in multiple heuristic optimization algorithms.For each case study,we analyze how the patterns are implemented in the algorithm and how they contribute to its performance.Through these case studies,we show how our analysis can be used to understand the behavior of heuristic optimization algorithms and guide the design of new algorithms.Our analysis reveals that patterns in heuristic optimization algorithms are essential to their effectiveness.By understanding and incorporating these patterns into the design of new algorithms,researchers can develop more efficient and effective optimization algorithms.
文摘Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm optimization （HPSO） algorithm is proposed to solve the decision-making （DM） problem. HA facilitates to search the local optimum in the neighborhood of a solution, while the PSO algorithm tends to explore the search space for possible solutions. Combining the advantages of HA and PSO, HPSO algorithms can find out the global optimum quickly and efficiently. It obtains the DM solution by seeking for the optimal assignment of missiles of friendly fighter aircrafts （FAs） to hostile FAs. Simulation results show that the proposed algorithm is superior to the general PSO algorithm and two GA based algorithms in searching for the best solution to the DM problem.
基金supported by the National Natural Science Foundation of China(No.62373027).
文摘In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms to solve the problem of multi-UAV path planning.The Dung Beetle Optimization(DBO)algorithm has been widely applied due to its diverse search patterns in the above algorithms.However,the update strategies for the rolling and thieving dung beetles of the DBO algorithm are overly simplistic,potentially leading to an inability to fully explore the search space and a tendency to converge to local optima,thereby not guaranteeing the discovery of the optimal path.To address these issues,we propose an improved DBO algorithm guided by the Landmark Operator(LODBO).Specifically,we first use tent mapping to update the population strategy,which enables the algorithm to generate initial solutions with enhanced diversity within the search space.Second,we expand the search range of the rolling ball dung beetle by using the landmark factor.Finally,by using the adaptive factor that changes with the number of iterations.,we improve the global search ability of the stealing dung beetle,making it more likely to escape from local optima.To verify the effectiveness of the proposed method,extensive simulation experiments are conducted,and the result shows that the LODBO algorithm can obtain the optimal path using the shortest time compared with the Genetic Algorithm(GA),the Gray Wolf Optimizer(GWO),the Whale Optimization Algorithm(WOA)and the original DBO algorithm in the disaster search and rescue task set.
文摘Lot scheduling problem with idle time transfer between processes to minimize mean flow time is very important because to minimize mean flow time is to minimize work in process. But the problem is NP hard and no polynomial algorithm exists to guarantee optimal solution. Based the analysis the mathematical structure of the problem, the paper presents a new heuristic algorithm. Computer simulation shows that the proposed heuristic algorithm performs well in terms of both quality of solution and execution speed.
基金The authors would like to extend their gratitude to King Saud University(Riyadh,Saudi Arabia)for funding this research through Researchers Supporting Project number(RSP-2021/260)And this work was supported by the Natural Science Foundation of Hunan Province,China(Grant No.2020JJ4949)the Postgraduate Scientific Research Innovation Project of Hunan Province(Grant No.CX20200883).
文摘Recently, the development of Industrial Internet of Things hastaken the advantage of 5G network to be more powerful and more intelligent.However, the upgrading of 5G network will cause a variety of issues increase,one of them is the increased cost of coverage. In this paper, we proposea sustainable wireless sensor networks system, which avoids the problemsbrought by 5G network system to some extent. In this system, deployingrelays and selecting routing are for the sake of communication and charging.The main aim is to minimize the total energy-cost of communication underthe precondition, where each terminal with low-power should be charged byat least one relay. Furthermore, from the perspective of graph theory, weextract a combinatorial optimization problem from this system. After that,as to four different cases, there are corresponding different versions of theproblem. We give the proofs of computational complexity for these problems,and two heuristic algorithms for one of them are proposed. Finally, theextensive experiments compare and demonstrate the performances of thesetwo algorithms.
文摘Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generated control overhead consists of controller-device and inter-controller communications to discover the network topology, exchange configurations, and set up and modify flow tables in the control plane. However, due to the high complexity of the proposed optimization model to the CPP, heuristic algorithms have been reported to find near-optimal solutions faster for large-scale wired networks. In this paper, the objective is to extend those existing heuristic algorithms to solve a proposed optimization model to the CPP in software-<span>defined multihop wireless networking</span><span> (SDMWN).</span>Our results demonstrate that using ranking degrees assigned to the possible controller placements, including the average distance to other devices as a degree or the connectivity degree of each placement, the extended heuristic algorithms are able to achieve the optimal solution in small-scale networks in terms of the generated control overhead and the number of controllers selected in the network. As a result, using extended heuristic algorithms, the average number of hops among devices and their assigned controllers as well as among controllers will be reduced. Moreover, these algorithms are able tolower<span "=""> </span>the control overhead in large-scale networks and select fewer controllers compared to an extended algorithm that solves the CPP in SDMWN based on a randomly selected controller placement approach.
文摘Resource-constrained project scheduling problem（RCPSP） is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities＇ cost with the resource constraints that is a critical sub-problem in partner selection of construction supply chain management because the capacities of the renewable resources supplied by the partners will effect on the project scheduling. Its mathematic model is presented firstly, and analysis on the characteristic of the problem shows that the objective function is non-regular and the problem is NP-complete following which the basic idea for solution is clarified. Based on a definition of preposing activity cost matrix, a heuristic algorithm is brought forward. Analyses on the complexity of the heuristics and the result of numerical studies show that the heuristic algorithm is feasible and relatively effective.
文摘We present a new algorithm for nesting problems.Many equally spaced points are set on a sheet,and a piece is moved to one of the points and rotated by an angle.Both the point and the rotation angle constitute the packing attitude of the piece.We propose a new algorithm named HAPE(Heuristic Algorithm based on the principle of minimum total Potential Energy) to find the optimal packing attitude at which the piece has the lowest center of gravity.In addition,a new technique for polygon overlap testing is proposed which avoids the time-consuming calculation of no-fit-polygon(NFP).The detailed implementation of HAPE is presented and two computational experiments are described.The first experiment is based on a real industrial problem and the second on 11 published benchmark problems.Using a hill-climbing(HC) search method,the proposed algorithm performs well in comparison with other published solutions.
文摘An optimal layout or three-dimensional spatial distribution of stopes guarantees the maximum profitability over life span of an underground mining operation.Thus,stope optimization is one of the key areas in underground mine planning practice.However,the computational complexity in developing an optimal stope layout has been a reason for limited availability of the algorithms offering solution to this problem.This article shares a new and efficient heuristic algorithm that considers a three-dimensional ore body model as an input,maximizes the economic value,and satisfies the physical mining and geotechnical constraints for generating an optimal stope layout.An implementation at a copper deposit demonstrates the applicability and robustness of the algorithm.A parallel processing based modification improving the performance of the original algorithm in terms of enormous computational time saving is also presented.
文摘A new heuristic algorithm is proposed for solving general integer linear programming problems. In the algorithm, the objective function hyperplane is used as a cutting plane, and then by introducing a special set of assistant sets, an efficient heuristic search for the solution to the integer linear program is carried out in the sets on the objective function hyperplane. A simple numerical example shows that the algorithm is efficient for some problems, and therefore, of practical interest.
文摘E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.
基金supported by the National Key Research and Development Program of China (Grant Nos. 2017YFA0403301, 2017YFB0503301, and2018YFB0504302)the National Natural Science Foundation of China (Grant Nos. 11991073, 61975229, and Y8JC011L51)+2 种基金the Key Program of CAS (Grant No. XDB17030500)the Civil Space Project (Grant No. D040301)the Science Challenge Project (Grant No. TZ2018005)。
文摘We report an overlapping sampling scheme to accelerate computational ghost imaging for imaging moving targets,based on reordering a set of Hadamard modulation matrices by means of a heuristic algorithm. The new condensed overlapped matrices are then designed to shorten and optimize encoding of the overlapped patterns, which are shown to be much superior to the random matrices. In addition, we apply deep learning to image the target, and use the signal acquired by the bucket detector and corresponding real image to train the neural network. Detailed comparisons show that our new method can improve the imaging speed by as much as an order of magnitude, and improve the image quality as well.
基金National Natural Science Foundations of China(Nos.71201171,71501179)
文摘The execution process of satellite-ground clock synchronization and ephemeris uploading in the system is analyzed,as well as their characterized operation and their relationship.Based on the analysis of the scheduling goal and constraint character,a heuristics rule-based multi-stage link scheduling algorithm was put forward.The algorithm distinguishes the on-off-frontier satellites from the others and schedules them by turns.The paper presented the main flow as well as the detailed design of the rule.Finally based on the current COMPASS global system,some typical resources and constraints are selected to generate an instance.Then the comparison analysis between the heuristics scheduling algorithm and three other traditional scheduling strategies are carried out.The result shows the validity and reasonability of the multi-stage strategy.
基金Project supported in part by the Fundamental Research Funds for the Central Universities (Grant No.2021JBZ107)the National Natural Science Foundation of China (Grant Nos.72288101 and 71931002)。
文摘This paper investigates traffic flow of connected and automated vehicles at lane drop on two-lane highway. We evaluate and compare performance of an optimization-based control algorithm(OCA) with that of a heuristic rules-based algorithm(HRA). In the OCA, the average speed of each vehicle is maximized. In the HRA, virtual vehicle and restriction of the command acceleration caused by the virtual vehicle are introduced. It is found that(i) capacity under the HRA(denoted as C_(H)) is smaller than capacity under the OCA;(ii) the travel delay is always smaller under the OCA, but driving is always much more comfortable under the HRA;(iii) when the inflow rate is smaller than C_(H), the HRA outperforms the OCA with respect to the fuel consumption and the monetary cost;(iv) when the inflow rate is larger than C_(H), the HRA initially performs better with respect to the fuel consumption and the monetary cost, but the OCA would become better after certain time. The spatiotemporal pattern and speed profile of traffic flow are presented, which explains the reason underlying the different performance. The study is expected to help for better understanding of the two different types of algorithm.
文摘This paper presents the two-machine flowshop group scheduling problem with the optimal objective of maximum lateness. A dominance rule within group and a dominance rule between groups are established. These dominance rules along with a previously established dominance rule are used to develop a heuristic algorithm. Experimental results are given and analyzed.
基金Sponsored by the Ministerial Level Advanced Research Foundation(11415133)
文摘To guarantee the optimal reduct set, a heuristic reduction algorithm is proposed, which considers the distinguishing information between the members of each pair decision classes. Firstly the pairwise positive region is defined, based on which the pairwise significance measure is calculated between the members of each pair classes. Finally the weighted pairwise significance of attribute is used as the attribute reduction criterion, which indicates the necessity of attributes very well. By introducing the noise tolerance factor, the new algorithm can tolerate noise to some extent. Experimental results show the advantages of our novel heuristic reduction algorithm over the traditional attribute dependency based algorithm.
文摘Based on a presented inference algorithm of fuzzy reasoning, a fuzzy reasoning system is made up. A method of modeling the fuzzy reasoning system, and the setting up of the reasoning knowledge based and reasoning rules are studied in this paper. Then a heuristic inference algorithm is presented according to the system.
文摘This framework proposes a heuristic algorithm based on LP （linear programming） for optimizing the electricity cost in large residential buildings, in a smart grid environment. Our heuristic tackles large multi-objective energy allocation problem （large number of appliances and high time resolution）. The primary goal is to reduce the electricity bills, and discomfort factor. Also, increase the utilization of domestic renewable energy, and reduce the running time of the optimization algorithm. Our heuristic algorithm uses linear programming relaxation, and two rounding strategies. The first technique, called CR （cumulative rounding）, is designed for thermostatic appliances such as air conditioners and electric heaters, and the second approach, called MCR （minimum cost rounding）, is designed for other interruptible appliances. The results show that the proposed heuristic algorithm can be used to solve large MILP （mixed integer linear programming） problems and gives a decent suboptimal solution in polynomial time.
文摘The communication resources scheduling problem of the satellite network contains the user-satellite association problem,the user-beam matching problem,and the beam power allocation problem.Different optimization problems contain different types of variables.Mult-type variables and three coupling problems cause the cooperative scheduling problem to be complex.In this paper,we propose a mixed vector encoding heuristic algorithm(MVEHA)to optimize the joint resources allocation problem of the multiple beams satellite network.Specifically,we use the 0-1 encoding vector to represent the user-satellite association scheme,the user-beam matching scheme is denoted by the continuous vector with priority,and a normalization vector is designed to encoded the beam power allocation scheme.Due to the mixed vector encoding method,we design two optimization operators to guide the search direction of the population.Compared to the conventional optimization algorithm,the simulation experiment shows MVEHA has better solution performance and robustness to solve the communication resources allocation problem of the satellite network.
