This work addresses the cut order planning(COP)problem for multi-color garment production,which is the first step in the clothing industry.First,a multi-objective optimization model of multicolor COP(MCOP)is establish...This work addresses the cut order planning(COP)problem for multi-color garment production,which is the first step in the clothing industry.First,a multi-objective optimization model of multicolor COP(MCOP)is established with production error and production cost as optimization objectives,combined with constraints such as the number of equipment and the number of layers.Second,a decoupled multi-objective optimization algorithm(DMOA)is proposed based on the linear programming decoupling strategy and non-dominated sorting in genetic algorithmsⅡ(NSGAII).The size-combination matrix and the fabric-layer matrix are decoupled to improve the accuracy of the algorithm.Meanwhile,an improved NSGAII algorithm is designed to obtain the optimal Pareto solution to the MCOP problem,thereby constructing a practical intelligent production optimization algorithm.Finally,the effectiveness and superiority of the proposed DMOA are verified through practical cases and comparative experiments,which can effectively optimize the production process for garment enterprises.展开更多
We study the fabric spreading and cutting problem in apparel factories.For the sake of saving the material costs,the cutting requirement should be met exactly without producing additional garment components.For reduci...We study the fabric spreading and cutting problem in apparel factories.For the sake of saving the material costs,the cutting requirement should be met exactly without producing additional garment components.For reducing the production costs,the number of lays that corresponds to the frequency of using the cutting beds should be minimized.We propose an iterated greedy algorithm for solving the fabric spreading and cutting problem.This algorithm contains a constructive procedure and an improving loop.Firstly the constructive procedure creates a set of lays in sequence,and then the improving loop tries to pick each lay from the lay set and rearrange the remaining lays into a smaller lay set.The improving loop will run until it cannot obtain any smaller lay set or the time limit is due.The experiment results on 500 cases show that the proposed algorithm is effective and efficient.展开更多
An improved genetic algorithm and its application to resolve cutting stock problem arc presented.It is common to apply simple genetic algorithm(SGA)to cutting stock problem,but the huge amount of computing of SGA is a...An improved genetic algorithm and its application to resolve cutting stock problem arc presented.It is common to apply simple genetic algorithm(SGA)to cutting stock problem,but the huge amount of computing of SGA is a serious problem in practical application.Accelerating genetic algorithm(AGA)based on integer coding and AGA's detailed steps are developed to reduce the amount of computation,and a new kind of rectangular parts blank layout algorithm is designed for rectangular cutting stock problem.SGA is adopted to produce individuals within given evolution process,and the variation interval of these individuals is taken as initial domain of the next optimization process,thus shrinks searching range intensively and accelerates the evaluation process of SGA.To enhance the diversity of population and to avoid the algorithm stagnates at local optimization result,fixed number of individuals are produced randomly and replace the same number of parents in every evaluation process.According to the computational experiment,it is observed that this improved GA converges much sooner than SGA,and is able to get the balance of good result and high efficiency in the process of optimization for rectangular cutting stock problem.展开更多
In this paper, a new probabilistic analytical approach, the minimal cut-based recursive decomposition algorithm （MCRDA）, is presented to evaluate the seismic reliability of large-scale lifeline systems. Based on the...In this paper, a new probabilistic analytical approach, the minimal cut-based recursive decomposition algorithm （MCRDA）, is presented to evaluate the seismic reliability of large-scale lifeline systems. Based on the minimal cut searching algorithm, the approach calculates the disjoint minimal cuts one by one using the basic procedure of the recursive decomposition method. At the same time, the process obtains the disjoint minimal paths of the system. In order to improve the computation efficiency, probabilistic inequality is used to calculate a solution that satisfies the prescribed error bound. A series of case studies show that MCRDA converges rapidly when the edges of the systems have low reliabilities. Therefore, the approach can be used to evaluate large-scale lifeline systems subjected to strong seismic wave excitation.展开更多
Balas and Mazzola linearization (BML) is widely used in devising cutting plane algorithms for quadratic 0-1 programs. In this article, we improve BML by first strengthening the primal formulation of BML and then consi...Balas and Mazzola linearization (BML) is widely used in devising cutting plane algorithms for quadratic 0-1 programs. In this article, we improve BML by first strengthening the primal formulation of BML and then considering the dual formulation. Additionally, a new cutting plane algorithm is proposed.展开更多
In order to realize the memory cutting of a shearer, made use of the memorizedcutting path and acquisitioned cutting parameters, and realized the teaching and playbackof the cutting path.In order to optimize the memor...In order to realize the memory cutting of a shearer, made use of the memorizedcutting path and acquisitioned cutting parameters, and realized the teaching and playbackof the cutting path.In order to optimize the memory cutting path of a shearer, took intoaccount the constraints of coal mining craft, coal quality and the adaption faculty of coalmining equipments.Genetic algorithm theory was used to optimize the memory cutting ofshearer and simulate with Matlab, and realized the most valuable mining recovery rate.The experimental results show that the optimization of the memory cutting path of ashearer based on the genetic algorithm is feasible and obtains the most valuable memorycutting path, improving the ability of shearer automatic cutting.展开更多
We consider the problem of guillotine cutting a rectangular sheet into rectangular pieces with two heights. A polynomial time algorithm for this problem is constructed.
This study presents a two-echelon inventory routing problem (2E-IRP) with an end-of-tour replenishment (ETR) policy whose distribution network consists of a supplier, several distribution centers (DCs) and several ret...This study presents a two-echelon inventory routing problem (2E-IRP) with an end-of-tour replenishment (ETR) policy whose distribution network consists of a supplier, several distribution centers (DCs) and several retailers on a multi-period planning horizon. A formulation of the problem based on vehicle indices is proposed in the form of a mixed integer linear program (MILP). The mathematical model of the problem is solved using a branch and cut (B&C) algorithm. The results of the tests are compared to the results of a branch and price (B&P) algorithm from the literature on 2E-IRP with a classical distribution policy. The results of the tests show that the B&C algorithm solves 197 out of 200 instances (98.5%). The comparison of the B&C and B&P results shows that 185 best solutions are obtained with the B&C algorithm on 197 instances (93.9%). Overall, the B&C algorithm achieves cost reductions ranging from 0.26% to 41.44% compared to the classic 2E-IRP results solved with the B&P algorithm, with an overall average reduction of 18.08%.展开更多
In response to the problems of low sampling efficiency,strong randomness of sampling points,and the tortuous shape of the planned path in the traditional rapidly-exploring random tree(RRT)algorithm and bidirectional R...In response to the problems of low sampling efficiency,strong randomness of sampling points,and the tortuous shape of the planned path in the traditional rapidly-exploring random tree(RRT)algorithm and bidirectional RRT algorithm used for unmanned aerial vehicle(UAV)path planning in complex environments,an improved bidirectional RRT algorithm was proposed.The algorithm firstly adopted a goal-oriented strategy to guide the sampling points towards the target point,and then the artificial potential field acted on the random tree nodes to avoid collision with obstacles and reduced the length of the search path,and the random tree node growth also combined the UAV’s own flight constraints,and by combining the triangulation method to remove the redundant node strategy and the third-order B-spline curve for the smoothing of the trajectory,the planned path was better.The planned paths were more optimized.Finally,the simulation experiments in complex and dynamic environments showed that the algorithm effectively improved the speed of trajectory planning and shortened the length of the trajectory,and could generate a safe,smooth and fast trajectory in complex environments,which could be applied to online trajectory planning.展开更多
High-speed milling(HSM)is advantageous for machining high-quality complex-structure surface components with various materials.Identifying and estimating cutting force signals for characterizing HSM is of high signific...High-speed milling(HSM)is advantageous for machining high-quality complex-structure surface components with various materials.Identifying and estimating cutting force signals for characterizing HSM is of high significance.However,considering the tool runout and size effects,many proposed models focus on the material and mechanical characteristics.This study presents a novel approach for predicting micromilling cutting forces using a semianalytical multidimensional model that integrates experimental empirical data and a mechanical theoretical force model.A novel analytical optimization approach is provided to identify the cutting forces,classify the cutting states,and determine the tool runout using an adaptive algorithm that simplifies modeling and calculation.The instantaneous un-deformed chip thickness(IUCT)is determined from the trochoidal trajectories of each tool flute and optimized using the bisection method.Herein,the computational efficiency is improved,and the errors are clarified.The tool runout parameters are identified from the processed displacement signals and determined from the preprocessed vibration signals using an adaptive signal processing method.It is reliable and stable for determining tool runout and is an effective foundation for the force model.This approach is verified using HSM tests.Herein,the determination coefficients are stable above 0.9.It is convenient and efficient for achieving the key intermediate parameters(IUCT and tool runout),which can be generalized to various machining conditions and operations.展开更多
The current extended fuzzy description logics lack reasoning algorithms with TBoxes. The problem of the satisfiability of the extended fuzzy description logic EFALC cut concepts w. r. t. TBoxes is proposed, and a reas...The current extended fuzzy description logics lack reasoning algorithms with TBoxes. The problem of the satisfiability of the extended fuzzy description logic EFALC cut concepts w. r. t. TBoxes is proposed, and a reasoning algorithm is given. This algorithm is designed in the style of tableau algorithms, which is usually used in classical description logics. The transformation rules and the process of this algorithm is described and optimized with three main techniques： recursive procedure call, branch cutting and introducing sets of mesne results. The optimized algorithm is proved sound, complete and with an EXPTime complexity, and the satisfiability problem is EXPTime-complete.展开更多
基金Supported by the Natural Science Foundation of Zhejiang Province(No.LQ22F030015).
文摘This work addresses the cut order planning(COP)problem for multi-color garment production,which is the first step in the clothing industry.First,a multi-objective optimization model of multicolor COP(MCOP)is established with production error and production cost as optimization objectives,combined with constraints such as the number of equipment and the number of layers.Second,a decoupled multi-objective optimization algorithm(DMOA)is proposed based on the linear programming decoupling strategy and non-dominated sorting in genetic algorithmsⅡ(NSGAII).The size-combination matrix and the fabric-layer matrix are decoupled to improve the accuracy of the algorithm.Meanwhile,an improved NSGAII algorithm is designed to obtain the optimal Pareto solution to the MCOP problem,thereby constructing a practical intelligent production optimization algorithm.Finally,the effectiveness and superiority of the proposed DMOA are verified through practical cases and comparative experiments,which can effectively optimize the production process for garment enterprises.
基金supported in part by the National Key Research and Development Program of China(2018YFB1702701)the National Natural Science Foundation of China(61773381,61773382,61533019,61702519)+3 种基金Dongguan’s Innovation Talents Project(Gang Xiong)Guangdong’s Science and Technology Project(2017B090912001)Beijing Natural Science Foundation(4182065)Chinese Hunan’s Science and Technology Project(20181040)
文摘We study the fabric spreading and cutting problem in apparel factories.For the sake of saving the material costs,the cutting requirement should be met exactly without producing additional garment components.For reducing the production costs,the number of lays that corresponds to the frequency of using the cutting beds should be minimized.We propose an iterated greedy algorithm for solving the fabric spreading and cutting problem.This algorithm contains a constructive procedure and an improving loop.Firstly the constructive procedure creates a set of lays in sequence,and then the improving loop tries to pick each lay from the lay set and rearrange the remaining lays into a smaller lay set.The improving loop will run until it cannot obtain any smaller lay set or the time limit is due.The experiment results on 500 cases show that the proposed algorithm is effective and efficient.
基金supported by National Natural Science Foundation of China(No.50575153)Provincial Key Technology Projects of Sichuan,China(No.03GG010-002)
文摘An improved genetic algorithm and its application to resolve cutting stock problem arc presented.It is common to apply simple genetic algorithm(SGA)to cutting stock problem,but the huge amount of computing of SGA is a serious problem in practical application.Accelerating genetic algorithm(AGA)based on integer coding and AGA's detailed steps are developed to reduce the amount of computation,and a new kind of rectangular parts blank layout algorithm is designed for rectangular cutting stock problem.SGA is adopted to produce individuals within given evolution process,and the variation interval of these individuals is taken as initial domain of the next optimization process,thus shrinks searching range intensively and accelerates the evaluation process of SGA.To enhance the diversity of population and to avoid the algorithm stagnates at local optimization result,fixed number of individuals are produced randomly and replace the same number of parents in every evaluation process.According to the computational experiment,it is observed that this improved GA converges much sooner than SGA,and is able to get the balance of good result and high efficiency in the process of optimization for rectangular cutting stock problem.
基金the Natural Science Fundation of China for the Innovative Research Group of China Under Grant No. 50621062
文摘In this paper, a new probabilistic analytical approach, the minimal cut-based recursive decomposition algorithm （MCRDA）, is presented to evaluate the seismic reliability of large-scale lifeline systems. Based on the minimal cut searching algorithm, the approach calculates the disjoint minimal cuts one by one using the basic procedure of the recursive decomposition method. At the same time, the process obtains the disjoint minimal paths of the system. In order to improve the computation efficiency, probabilistic inequality is used to calculate a solution that satisfies the prescribed error bound. A series of case studies show that MCRDA converges rapidly when the edges of the systems have low reliabilities. Therefore, the approach can be used to evaluate large-scale lifeline systems subjected to strong seismic wave excitation.
文摘Balas and Mazzola linearization (BML) is widely used in devising cutting plane algorithms for quadratic 0-1 programs. In this article, we improve BML by first strengthening the primal formulation of BML and then considering the dual formulation. Additionally, a new cutting plane algorithm is proposed.
基金Supported by the High-Tech Research and Development Program of China(2008AA062202)Fok Ying Tung Education Foundation(114003)New Teacher Foundation for the Doctoral Program of Ministry of Education(20070290538)
文摘In order to realize the memory cutting of a shearer, made use of the memorizedcutting path and acquisitioned cutting parameters, and realized the teaching and playbackof the cutting path.In order to optimize the memory cutting path of a shearer, took intoaccount the constraints of coal mining craft, coal quality and the adaption faculty of coalmining equipments.Genetic algorithm theory was used to optimize the memory cutting ofshearer and simulate with Matlab, and realized the most valuable mining recovery rate.The experimental results show that the optimization of the memory cutting path of ashearer based on the genetic algorithm is feasible and obtains the most valuable memorycutting path, improving the ability of shearer automatic cutting.
文摘We consider the problem of guillotine cutting a rectangular sheet into rectangular pieces with two heights. A polynomial time algorithm for this problem is constructed.
文摘This study presents a two-echelon inventory routing problem (2E-IRP) with an end-of-tour replenishment (ETR) policy whose distribution network consists of a supplier, several distribution centers (DCs) and several retailers on a multi-period planning horizon. A formulation of the problem based on vehicle indices is proposed in the form of a mixed integer linear program (MILP). The mathematical model of the problem is solved using a branch and cut (B&C) algorithm. The results of the tests are compared to the results of a branch and price (B&P) algorithm from the literature on 2E-IRP with a classical distribution policy. The results of the tests show that the B&C algorithm solves 197 out of 200 instances (98.5%). The comparison of the B&C and B&P results shows that 185 best solutions are obtained with the B&C algorithm on 197 instances (93.9%). Overall, the B&C algorithm achieves cost reductions ranging from 0.26% to 41.44% compared to the classic 2E-IRP results solved with the B&P algorithm, with an overall average reduction of 18.08%.
基金supported by Gansu Provincial Science and Technology Program Project(No.23JRRA868)Lanzhou Municipal Talent Innovation and Entrepreneurship Project(No.2019-RC-103)。
文摘In response to the problems of low sampling efficiency,strong randomness of sampling points,and the tortuous shape of the planned path in the traditional rapidly-exploring random tree(RRT)algorithm and bidirectional RRT algorithm used for unmanned aerial vehicle(UAV)path planning in complex environments,an improved bidirectional RRT algorithm was proposed.The algorithm firstly adopted a goal-oriented strategy to guide the sampling points towards the target point,and then the artificial potential field acted on the random tree nodes to avoid collision with obstacles and reduced the length of the search path,and the random tree node growth also combined the UAV’s own flight constraints,and by combining the triangulation method to remove the redundant node strategy and the third-order B-spline curve for the smoothing of the trajectory,the planned path was better.The planned paths were more optimized.Finally,the simulation experiments in complex and dynamic environments showed that the algorithm effectively improved the speed of trajectory planning and shortened the length of the trajectory,and could generate a safe,smooth and fast trajectory in complex environments,which could be applied to online trajectory planning.
基金Supported by National Natural Science Foundation of China(Grant No.52175528).
文摘High-speed milling(HSM)is advantageous for machining high-quality complex-structure surface components with various materials.Identifying and estimating cutting force signals for characterizing HSM is of high significance.However,considering the tool runout and size effects,many proposed models focus on the material and mechanical characteristics.This study presents a novel approach for predicting micromilling cutting forces using a semianalytical multidimensional model that integrates experimental empirical data and a mechanical theoretical force model.A novel analytical optimization approach is provided to identify the cutting forces,classify the cutting states,and determine the tool runout using an adaptive algorithm that simplifies modeling and calculation.The instantaneous un-deformed chip thickness(IUCT)is determined from the trochoidal trajectories of each tool flute and optimized using the bisection method.Herein,the computational efficiency is improved,and the errors are clarified.The tool runout parameters are identified from the processed displacement signals and determined from the preprocessed vibration signals using an adaptive signal processing method.It is reliable and stable for determining tool runout and is an effective foundation for the force model.This approach is verified using HSM tests.Herein,the determination coefficients are stable above 0.9.It is convenient and efficient for achieving the key intermediate parameters(IUCT and tool runout),which can be generalized to various machining conditions and operations.
基金The National Natural Science Foundation of China(No60403016),the Weaponry Equipment Foundation of PLA Equip-ment Ministry (No51406020105JB8103)
文摘The current extended fuzzy description logics lack reasoning algorithms with TBoxes. The problem of the satisfiability of the extended fuzzy description logic EFALC cut concepts w. r. t. TBoxes is proposed, and a reasoning algorithm is given. This algorithm is designed in the style of tableau algorithms, which is usually used in classical description logics. The transformation rules and the process of this algorithm is described and optimized with three main techniques： recursive procedure call, branch cutting and introducing sets of mesne results. The optimized algorithm is proved sound, complete and with an EXPTime complexity, and the satisfiability problem is EXPTime-complete.
