The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency...The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency. A multi-objective model was presented for the material distribution routing problem in mixed manufacturing systems, and it was solved by a hybrid multi-objective evolutionary algorithm (HMOEA). The characteristics of the HMOEA are as follows: 1) A route pool is employed to preserve the best routes for the population initiation; 2) A specialized best?worst route crossover (BWRC) mode is designed to perform the crossover operators for selecting the best route from Chromosomes 1 to exchange with the worst one in Chromosomes 2, so that the better genes are inherited to the offspring; 3) A route swap mode is used to perform the mutation for improving the convergence speed and preserving the better gene; 4) Local heuristics search methods are applied in this algorithm. Computational study of a practical case shows that the proposed algorithm can decrease the total travel distance by 51.66%, enhance the average vehicle load rate by 37.85%, cut down 15 routes and reduce a deliver vehicle. The convergence speed of HMOEA is faster than that of famous NSGA-II.展开更多
Dear Editor,This letter focuses on the distributed cooperative regulation problem for a class of networked re-entrant manufacturing systems(RMSs).The networked system is structured with a three-tier architecture:the p...Dear Editor,This letter focuses on the distributed cooperative regulation problem for a class of networked re-entrant manufacturing systems(RMSs).The networked system is structured with a three-tier architecture:the production line,the manufacturing layer and the workshop layer.The dynamics of re-entrant production lines are governed by hyperbolic partial differential equations(PDEs)based on the law of mass conservation.展开更多
In this work, we prove the existence and uniqueness of the solution of the generalized Schrödinger equation in the periodic distributional space P’. Furthermore, we prove that the solution depends continuously r...In this work, we prove the existence and uniqueness of the solution of the generalized Schrödinger equation in the periodic distributional space P’. Furthermore, we prove that the solution depends continuously respect to the initial data in P’. Introducing a family of weakly continuous operators, we prove that this family is a semigroup of operators in P’. Then, with this family of operators, we get a fine version of the existence and dependency continuous theorem obtained. Finally, we provide some consequences of this study.展开更多
Several industrial coal processes are largely determined by the distribution of particle sizes in their feed.Currently these parameters are measured by manual sampling,which is time consuming and cannot provide real t...Several industrial coal processes are largely determined by the distribution of particle sizes in their feed.Currently these parameters are measured by manual sampling,which is time consuming and cannot provide real time feedback for automatic control purposes.In this paper,an approach using image segmentation on images of overlapped coal particles is described.The estimation of the particle size distribution by number is also described.The particle overlap problem was solved using image enhancement algorithms that converted those image parts representing material in lower layers to black.Exponential high-pass filter(EHPF) algorithms were used to remove the texture from particles on the surface.Finally,the edges of the surface particles were identified by morphological edge detection.These algorithms are described in detail as is the method of extracting the coal particle size.Tests indicate that using more coal images gives a higher accuracy estimate.The positive absolute error of 50 random tests was consistently less than 2.5% and the errors were reduced as the size of the fraction increased.展开更多
The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worke...The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worker constraints.As one critical factor of production,effective utilization of worker resources can increase productivity.Meanwhile,energy consumption is a growing concern due to the increasingly serious environmental issues.Therefore,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this paper.To solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling schemes.To further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are proposed.These strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto solutions.The effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 instances.The results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.展开更多
In the manufacturing industry,reasonable scheduling can greatly improve production efficiency,while excessive resource consumption highlights the growing significance of energy conservation in production.This paper st...In the manufacturing industry,reasonable scheduling can greatly improve production efficiency,while excessive resource consumption highlights the growing significance of energy conservation in production.This paper studies the problem of energy-efficient distributed heterogeneous permutation flowshop problem with variable processing speed(DHPFSP-VPS),considering both the minimum makespan and total energy consumption(TEC)as objectives.A discrete multi-objective squirrel search algorithm(DMSSA)is proposed to solve the DHPFSPVPS.DMSSA makes four improvements based on the squirrel search algorithm.Firstly,in terms of the population initialization strategy,four hybrid initialization methods targeting different objectives are proposed to enhance the quality of initial solutions.Secondly,enhancements are made to the population hierarchy system and position updating methods of the squirrel search algorithm,making it more suitable for discrete scheduling problems.Additionally,regarding the search strategy,six local searches are designed based on problem characteristics to enhance search capability.Moreover,a dynamic predator strategy based on Q-learning is devised to effectively balance DMSSA’s capability for global exploration and local exploitation.Finally,two speed control energy-efficient strategies are designed to reduce TEC.Extensive comparative experiments are conducted in this paper to validate the effectiveness of the proposed strategies.The results of comparing DMSSA with other algorithms demonstrate its superior performance and its potential for efficient solving of the DHPFSP-VPS problem.展开更多
In this study, a distributed optimal control problem for n × n cooperative hyperbolic systems with infinite order operators and Dirichlet conditions are considered. The existence and uniqueness of the state of th...In this study, a distributed optimal control problem for n × n cooperative hyperbolic systems with infinite order operators and Dirichlet conditions are considered. The existence and uniqueness of the state of these systems are proved. The necessary and sufficient conditions for optimality of distributed control with constraints are found, and the set of equations and inequalities that defining the optimal control of these systems is also obtained. Finally, some examples for the control problem without constraints are given.展开更多
Currently,manufacturing enterprises face increasingly fierce market competition due to the various demands of customers and the rapid development of economic globalization.Hence,they have to extend their production mo...Currently,manufacturing enterprises face increasingly fierce market competition due to the various demands of customers and the rapid development of economic globalization.Hence,they have to extend their production mode into distributed environments and establish multiple factories in various geographical locations.Nowadays,distributed manufacturing systems have been widely adopted in industrial production processes.In recent years,many studies have been done on the modeling and optimization of distributed scheduling problems.This work provides a literature review on distributed scheduling problems in intelligent manufacturing systems.By summarizing and evaluating existing studies on distributed scheduling problems,we analyze the achievements and current research status in this field and discuss ongoing studies.Insights regarding prior works are discussed to uncover future research directions,particularly swarm intelligence and evolutionary algorithms,which are used for managing distributed scheduling problems in manufacturing systems.This work focuses on journal papers discovered using Google Scholar.After reviewing the papers,in this work,we discuss the research trends of distributed scheduling problems and point out some directions for future studies.展开更多
This paper considers a distributed nonsmooth resource allocation problem of minimizing a global convex function formed by a sum of local nonsmooth convex functions with coupled constraints.A distributed communication-...This paper considers a distributed nonsmooth resource allocation problem of minimizing a global convex function formed by a sum of local nonsmooth convex functions with coupled constraints.A distributed communication-efficient mirror-descent algorithm,which can reduce communication rounds between agents over the network,is designed for the distributed resource allocation problem.By employing communication-sliding methods,agents can find aε-solution in O(1/ε)communication rounds while maintaining O(1/ε^(2))subgradient evaluations for nonsmooth convex functions.A numerical example is also given to illustrate the effectiveness of the proposed algorithm.展开更多
Dear Editor,This letter studies the event-triggered adaptive horizon distributed model predictive control problem for discrete-time coupled nonlinear systems with additive disturbances.By constructing a new dualmodel ...Dear Editor,This letter studies the event-triggered adaptive horizon distributed model predictive control problem for discrete-time coupled nonlinear systems with additive disturbances.By constructing a new dualmodel optimal control problem,an event-triggered mechanism and an adaptive prediction horizon scheme are co-designed in the proposed scheme.Notably,the upper bound of the triggering interval remains independent of the dynamically shrinking prediction horizon.This enables the event-triggered mechanism to operate effectively even when the prediction horizon becomes zero,thus achieving cost savings throughout the control process.In addition,the sufficient conditions of the proposed scheme associated with the feasibility and stability are provided.The effectiveness is illustrated through a practical example.展开更多
This paper considers the simultaneous attack problem of multiple missiles against a maneuvering target. Different from most of the existing literature in which the simultaneous attack problem is formulated as a consen...This paper considers the simultaneous attack problem of multiple missiles against a maneuvering target. Different from most of the existing literature in which the simultaneous attack problem is formulated as a consensus problem of missiles＇ time-to-go estimates, this paper formulates it as the consensus problem of missiles＇ ranges-to-go. Based on this strategy, novel distributed guidance laws are proposed to solve the simultaneous attack problem with the target of unknown maneuverability.Adaptive control method is introduced to estimate the upper bound of the target＇s acceleration. The effectiveness of the proposed guidance laws is verified both theoretically and numerically.展开更多
An improved quantum-behaved particle swarm optimization （IQPSO） algorithm is employed to deter- mine aerosol size distribution （ASD）. The direct problem is solved using the anomalous diffraction approximation and ...An improved quantum-behaved particle swarm optimization （IQPSO） algorithm is employed to deter- mine aerosol size distribution （ASD）. The direct problem is solved using the anomalous diffraction approximation and Lambert-Beer＇s Law. Compared with the standard particle swarm optimization algo- rithm, the stochastic particle size optimization algorithm and the original QPSO, our IQPSO has faster convergence speed and higher accuracy within a smaller number of generations. Optimization param- eters for the IQPSO were also evaluated; we recommend using four measurement wavelengths and S0 particles. Size distributions of various aerosol types were estimated using the IQPSO under dependent and independent models. Finally, experimental ASDs at different locations in Harbin were recovered using the IQPSO. All our results confirm that the IQpSO algorithm is an effective and reliable technique for estimatinz ASD.展开更多
Conflicts between two or more parties arise for various reasons andperspectives. Thus, resolution of con-flicts frequently relies on some form of negotiation. Thispaper presents a general problem-solving framework for...Conflicts between two or more parties arise for various reasons andperspectives. Thus, resolution of con-flicts frequently relies on some form of negotiation. Thispaper presents a general problem-solving framework for modeling multi-issue multilateral negotiationusing fuzzy constraints. Agent negotiation is formulated as a distributed fuzzy constraintsatisfaction problem (DFCSP). Fuzzy constrains are thus used to naturally represent each agent''sdesires involving imprecision and human conceptualization, particularly when lexical imprecision andsubjective matters are concerned. On the other hand, based on fuzzy constraint-basedproblem-solving, our approach enables an agent not only to systematically relax fuzzy constraints togenerate a proposal, but also to employ fuzzy similarity to select the alternative that is subjectto its acceptability by the opponents. This task of problem-solving is to reach an agreement thatbenefits all agents with a high satisfaction degree of fuzzy constraints, and move towards the dealmore quickly since their search focuses only on the feasible solution space. An application tomultilateral negotiation of a travel planning is provided to demonstrate the usefulness andeffectiveness of our framework.展开更多
基金Project(50775089)supported by the National Natural Science Foundation of ChinaProject(2007AA04Z190,2009AA043301)supported by the National High Technology Research and Development Program of ChinaProject(2005CB724100)supported by the National Basic Research Program of China
文摘The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency. A multi-objective model was presented for the material distribution routing problem in mixed manufacturing systems, and it was solved by a hybrid multi-objective evolutionary algorithm (HMOEA). The characteristics of the HMOEA are as follows: 1) A route pool is employed to preserve the best routes for the population initiation; 2) A specialized best?worst route crossover (BWRC) mode is designed to perform the crossover operators for selecting the best route from Chromosomes 1 to exchange with the worst one in Chromosomes 2, so that the better genes are inherited to the offspring; 3) A route swap mode is used to perform the mutation for improving the convergence speed and preserving the better gene; 4) Local heuristics search methods are applied in this algorithm. Computational study of a practical case shows that the proposed algorithm can decrease the total travel distance by 51.66%, enhance the average vehicle load rate by 37.85%, cut down 15 routes and reduce a deliver vehicle. The convergence speed of HMOEA is faster than that of famous NSGA-II.
文摘Dear Editor,This letter focuses on the distributed cooperative regulation problem for a class of networked re-entrant manufacturing systems(RMSs).The networked system is structured with a three-tier architecture:the production line,the manufacturing layer and the workshop layer.The dynamics of re-entrant production lines are governed by hyperbolic partial differential equations(PDEs)based on the law of mass conservation.
文摘In this work, we prove the existence and uniqueness of the solution of the generalized Schrödinger equation in the periodic distributional space P’. Furthermore, we prove that the solution depends continuously respect to the initial data in P’. Introducing a family of weakly continuous operators, we prove that this family is a semigroup of operators in P’. Then, with this family of operators, we get a fine version of the existence and dependency continuous theorem obtained. Finally, we provide some consequences of this study.
基金the Creative Research Groups Science Fund of the National Natural Science Foundation of China(No.50921002)
文摘Several industrial coal processes are largely determined by the distribution of particle sizes in their feed.Currently these parameters are measured by manual sampling,which is time consuming and cannot provide real time feedback for automatic control purposes.In this paper,an approach using image segmentation on images of overlapped coal particles is described.The estimation of the particle size distribution by number is also described.The particle overlap problem was solved using image enhancement algorithms that converted those image parts representing material in lower layers to black.Exponential high-pass filter(EHPF) algorithms were used to remove the texture from particles on the surface.Finally,the edges of the surface particles were identified by morphological edge detection.These algorithms are described in detail as is the method of extracting the coal particle size.Tests indicate that using more coal images gives a higher accuracy estimate.The positive absolute error of 50 random tests was consistently less than 2.5% and the errors were reduced as the size of the fraction increased.
基金supported by the Natural Science Foundation of Anhui Province(Grant Number 2208085MG181)the Science Research Project of Higher Education Institutions in Anhui Province,Philosophy and Social Sciences(Grant Number 2023AH051063)the Open Fund of Key Laboratory of Anhui Higher Education Institutes(Grant Number CS2021-ZD01).
文摘The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worker constraints.As one critical factor of production,effective utilization of worker resources can increase productivity.Meanwhile,energy consumption is a growing concern due to the increasingly serious environmental issues.Therefore,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this paper.To solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling schemes.To further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are proposed.These strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto solutions.The effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 instances.The results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.
基金supported by the Key Research and Development Project of Hubei Province(Nos.2020BAB114 and 2023BAB094).
文摘In the manufacturing industry,reasonable scheduling can greatly improve production efficiency,while excessive resource consumption highlights the growing significance of energy conservation in production.This paper studies the problem of energy-efficient distributed heterogeneous permutation flowshop problem with variable processing speed(DHPFSP-VPS),considering both the minimum makespan and total energy consumption(TEC)as objectives.A discrete multi-objective squirrel search algorithm(DMSSA)is proposed to solve the DHPFSPVPS.DMSSA makes four improvements based on the squirrel search algorithm.Firstly,in terms of the population initialization strategy,four hybrid initialization methods targeting different objectives are proposed to enhance the quality of initial solutions.Secondly,enhancements are made to the population hierarchy system and position updating methods of the squirrel search algorithm,making it more suitable for discrete scheduling problems.Additionally,regarding the search strategy,six local searches are designed based on problem characteristics to enhance search capability.Moreover,a dynamic predator strategy based on Q-learning is devised to effectively balance DMSSA’s capability for global exploration and local exploitation.Finally,two speed control energy-efficient strategies are designed to reduce TEC.Extensive comparative experiments are conducted in this paper to validate the effectiveness of the proposed strategies.The results of comparing DMSSA with other algorithms demonstrate its superior performance and its potential for efficient solving of the DHPFSP-VPS problem.
文摘In this study, a distributed optimal control problem for n × n cooperative hyperbolic systems with infinite order operators and Dirichlet conditions are considered. The existence and uniqueness of the state of these systems are proved. The necessary and sufficient conditions for optimality of distributed control with constraints are found, and the set of equations and inequalities that defining the optimal control of these systems is also obtained. Finally, some examples for the control problem without constraints are given.
基金supported in part by the National Natural Science Foundation of China(Nos.61603169,61703220,and 61873328)China Postdoctoral Science Foundation Funded Project(No.2019T120569)+3 种基金Shandong Province Outstanding Youth Innovation Team Project of Colleges and Universities of China(No.2020RWG011)Shandong Province Colleges and Universities Youth Innovation Talent Introduction and Education Programthe Faculty Research Grants(FRG)from Macao University of Science and TechnologyShandong Provincial Key Laboratory for Novel Distributed Computer Software Technology。
文摘Currently,manufacturing enterprises face increasingly fierce market competition due to the various demands of customers and the rapid development of economic globalization.Hence,they have to extend their production mode into distributed environments and establish multiple factories in various geographical locations.Nowadays,distributed manufacturing systems have been widely adopted in industrial production processes.In recent years,many studies have been done on the modeling and optimization of distributed scheduling problems.This work provides a literature review on distributed scheduling problems in intelligent manufacturing systems.By summarizing and evaluating existing studies on distributed scheduling problems,we analyze the achievements and current research status in this field and discuss ongoing studies.Insights regarding prior works are discussed to uncover future research directions,particularly swarm intelligence and evolutionary algorithms,which are used for managing distributed scheduling problems in manufacturing systems.This work focuses on journal papers discovered using Google Scholar.After reviewing the papers,in this work,we discuss the research trends of distributed scheduling problems and point out some directions for future studies.
基金supported by the National Natural Science Foundation of China under Grant Nos.72101026,61621063the State Key Laboratory of Intelligent Control and Decision of Complex Systems。
文摘This paper considers a distributed nonsmooth resource allocation problem of minimizing a global convex function formed by a sum of local nonsmooth convex functions with coupled constraints.A distributed communication-efficient mirror-descent algorithm,which can reduce communication rounds between agents over the network,is designed for the distributed resource allocation problem.By employing communication-sliding methods,agents can find aε-solution in O(1/ε)communication rounds while maintaining O(1/ε^(2))subgradient evaluations for nonsmooth convex functions.A numerical example is also given to illustrate the effectiveness of the proposed algorithm.
基金supported by the National Natural Science Foundation of China(62473265,62476176,12426311).
文摘Dear Editor,This letter studies the event-triggered adaptive horizon distributed model predictive control problem for discrete-time coupled nonlinear systems with additive disturbances.By constructing a new dualmodel optimal control problem,an event-triggered mechanism and an adaptive prediction horizon scheme are co-designed in the proposed scheme.Notably,the upper bound of the triggering interval remains independent of the dynamically shrinking prediction horizon.This enables the event-triggered mechanism to operate effectively even when the prediction horizon becomes zero,thus achieving cost savings throughout the control process.In addition,the sufficient conditions of the proposed scheme associated with the feasibility and stability are provided.The effectiveness is illustrated through a practical example.
基金supported by the National Natural Science Foundation of China under Grant Nos.61473005,11332001,and 61471242the Research Project Fund under Grant No.17-163-11-ZT-003-018-01+2 种基金the Air Force Advance Research Fund under Grant No.303020503the Joint Fund of Equipment development and Aerospace Science and Technology under Grant No.6141B0624050101the National Defense Basic Scientific Research Program(Major)of China
文摘This paper considers the simultaneous attack problem of multiple missiles against a maneuvering target. Different from most of the existing literature in which the simultaneous attack problem is formulated as a consensus problem of missiles＇ time-to-go estimates, this paper formulates it as the consensus problem of missiles＇ ranges-to-go. Based on this strategy, novel distributed guidance laws are proposed to solve the simultaneous attack problem with the target of unknown maneuverability.Adaptive control method is introduced to estimate the upper bound of the target＇s acceleration. The effectiveness of the proposed guidance laws is verified both theoretically and numerically.
基金Support from the National Natural Science Foundation of China （No. 51476043）, the Major National Scientific Instruments and Equipment Development Special Foundation of China （No. 51327803） and the Foundation for Innovative Research Groups of the National Natural Science Foundation of China （No. 51421063） is gratefully acknowledged.
文摘An improved quantum-behaved particle swarm optimization （IQPSO） algorithm is employed to deter- mine aerosol size distribution （ASD）. The direct problem is solved using the anomalous diffraction approximation and Lambert-Beer＇s Law. Compared with the standard particle swarm optimization algo- rithm, the stochastic particle size optimization algorithm and the original QPSO, our IQPSO has faster convergence speed and higher accuracy within a smaller number of generations. Optimization param- eters for the IQPSO were also evaluated; we recommend using four measurement wavelengths and S0 particles. Size distributions of various aerosol types were estimated using the IQPSO under dependent and independent models. Finally, experimental ASDs at different locations in Harbin were recovered using the IQPSO. All our results confirm that the IQpSO algorithm is an effective and reliable technique for estimatinz ASD.
文摘Conflicts between two or more parties arise for various reasons andperspectives. Thus, resolution of con-flicts frequently relies on some form of negotiation. Thispaper presents a general problem-solving framework for modeling multi-issue multilateral negotiationusing fuzzy constraints. Agent negotiation is formulated as a distributed fuzzy constraintsatisfaction problem (DFCSP). Fuzzy constrains are thus used to naturally represent each agent''sdesires involving imprecision and human conceptualization, particularly when lexical imprecision andsubjective matters are concerned. On the other hand, based on fuzzy constraint-basedproblem-solving, our approach enables an agent not only to systematically relax fuzzy constraints togenerate a proposal, but also to employ fuzzy similarity to select the alternative that is subjectto its acceptability by the opponents. This task of problem-solving is to reach an agreement thatbenefits all agents with a high satisfaction degree of fuzzy constraints, and move towards the dealmore quickly since their search focuses only on the feasible solution space. An application tomultilateral negotiation of a travel planning is provided to demonstrate the usefulness andeffectiveness of our framework.
