A self-adaptive large neighborhood search method for scheduling n jobs on m non-identical parallel machines with mul- tiple time windows is presented. The problems＇ another feature lies in oversubscription, namely no...A self-adaptive large neighborhood search method for scheduling n jobs on m non-identical parallel machines with mul- tiple time windows is presented. The problems＇ another feature lies in oversubscription, namely not all jobs can be scheduled within specified scheduling horizons due to the limited machine capacity. The objective is thus to maximize the overall profits of processed jobs while respecting machine constraints. A first-in- first-out heuristic is applied to find an initial solution, and then a large neighborhood search procedure is employed to relax and re- optimize cumbersome solutions. A machine learning mechanism is also introduced to converge on the most efficient neighborhoods for the problem. Extensive computational results are presented based on data from an application involving the daily observation scheduling of a fleet of earth observing satellites. The method rapidly solves most problem instances to optimal or near optimal and shows a robust performance in sensitive analysis.展开更多
Focusing on the single machine scheduling problem which minimizes the total completion time in the presence of dynamic job arrivals, a rolling optimization scheduling algorithm is proposed based on the analysis of the...Focusing on the single machine scheduling problem which minimizes the total completion time in the presence of dynamic job arrivals, a rolling optimization scheduling algorithm is proposed based on the analysis of the character and structure of scheduling. An optimal scheduling strategy in collision window is presented. Performance evaluation of this algorithm is given. Simulation indicates that the proposed algorithm is better than other common heuristic algorithms on both the total performance and stability.展开更多
In the cloud data centers,how to map virtual machines(VMs) on physical machines(PMs) to reduce the energy consumption is becoming one of the major issues,and the existing VM scheduling schemes are mostly to reduce ene...In the cloud data centers,how to map virtual machines(VMs) on physical machines(PMs) to reduce the energy consumption is becoming one of the major issues,and the existing VM scheduling schemes are mostly to reduce energy consumption by optimizing the utilization of physical servers or network elements.However,the aggressive consolidation of these resources may lead to network performance degradation.In view of this,this paper proposes a two-stage VM scheduling scheme:(1) We propose a static VM placement scheme to minimize the number of activating PMs and network elements to reduce the energy consumption;(2) In the premise of minimizing the migration costs,we propose a dynamic VM migration scheme to minimize the maximum link utilization to improve the network performance.This scheme makes a tradeoff between energy efficiency and network performance.We design a new twostage heuristic algorithm for a solution,and the simulations show that our solution achieves good results.展开更多
The scheduling efficiency of the tracking and data relay satellite system（TDRSS）is strictly limited by the scheduling degrees of freedom（DoF）,including time DoF defined by jobs＇ flexible time windows and spatial ...The scheduling efficiency of the tracking and data relay satellite system（TDRSS）is strictly limited by the scheduling degrees of freedom（DoF）,including time DoF defined by jobs＇ flexible time windows and spatial DoF brought by multiple servable tracking and data relay satellites（TDRSs）.In this paper,ageneralized multiple time windows（GMTW）model is proposed to fully exploit the time and spatial DoF.Then,the improvements of service capability and job-completion probability based on the GMTW are theoretically proved.Further,an asymmetric path-relinking（APR）based heuristic job scheduling framework is presented to maximize the usage of DoF provided by the GMTW.Simulation results show that by using our proposal 11%improvement of average jobcompletion probability can be obtained.Meanwhile,the computing time of the time-to-target can be shorten to 1/9 of the GRASP.展开更多
A method for modeling the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure is provided. For the given n jobs to be processed on m machines, it is assum...A method for modeling the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure is provided. For the given n jobs to be processed on m machines, it is assumed that the processing times and the due dates are nonnegative fuzzy numbers and all the weights are positive, crisp numbers. Based on credibility measure, three parallel machine scheduling problems and a goal-programming model are formulated. Feasible schedules are evaluated not only by their objective values but also by the credibility degree of satisfaction with their precedence constraints. The genetic algorithm is utilized to find the best solutions in a short period of time. An illustrative numerical example is also given. Simulation results show that the proposed models are effective, which can deal with the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure.展开更多
Unrelated parallel machine scheduling problem(UPMSP)is a typical scheduling one and UPMSP with various reallife constraints such as additional resources has been widely studied;however,UPMSP with additional resources,...Unrelated parallel machine scheduling problem(UPMSP)is a typical scheduling one and UPMSP with various reallife constraints such as additional resources has been widely studied;however,UPMSP with additional resources,maintenance,and energy-related objectives is seldom investigated.The Artificial Bee Colony(ABC)algorithm has been successfully applied to various production scheduling problems and demonstrates potential search advantages in solving UPMSP with additional resources,among other factors.In this study,an energy-efficient UPMSP with additional resources and maintenance is considered.A dynamical artificial bee colony(DABC)algorithm is presented to minimize makespan and total energy consumption simultaneously.Three heuristics are applied to produce the initial population.Employed bee swarm and onlooker bee swarm are constructed.Computing resources are shifted from the dominated solutions to non-dominated solutions in each swarm when the given condition is met.Dynamical employed bee phase is implemented by computing resource shifting and solution migration.Computing resource shifting and feedback are used to construct dynamical onlooker bee phase.Computational experiments are conducted on 300 instances from the literature and three comparative algorithms and ABC are compared after parameter settings of all algorithms are given.The computational results demonstrate that the new strategies of DABC are effective and that DABC has promising advantages in solving the considered UPMSP.展开更多
It is a NP-hard problem to schedule a list of nonresumable jobs to the available intervals of an availability-constrained single machine to minimize the scheduling length. This paper transformed this scheduling proble...It is a NP-hard problem to schedule a list of nonresumable jobs to the available intervals of an availability-constrained single machine to minimize the scheduling length. This paper transformed this scheduling problem into a variant of the variable-sized bin packing problem, put forward eight bin packing algorithms adapted from the classic one-dimensional bin packing problem and investigated their performances from both of the worst-case and the average-case scenarios. Analytical results show that the worst-case performance ratios of the algorithms are not less than 2. Experimental results for average cases show that the Best Fit and the Best Fit Decreasing algorithm outperform any others for independent and precedence-constrained jobs respectively.展开更多
The optimality of a fuzzy logic alternative to the usual treatment of uncertainties in a scheduling system using fuzzy numbers is examined formally. Processing times and due dates are fuzzified and presented by fuzzy ...The optimality of a fuzzy logic alternative to the usual treatment of uncertainties in a scheduling system using fuzzy numbers is examined formally. Processing times and due dates are fuzzified and presented by fuzzy numbers. With introducing the necessity measure, we compare fuzzy completion times of jobs with fuzzy due dates to decide whether jobs are tardy. The object is to minimize the numbers of tardy jobs. The efficient solution method for this problem is proposed. And deterministic counterpart of this single machine scheduling problem is a special case of fuzzy version.展开更多
In order to improve the scheduling efficiency of photolithography,bottleneck process of wafer fabrications in the semiconductor industry,an effective estimation of distribution algorithm is proposed for scheduling pro...In order to improve the scheduling efficiency of photolithography,bottleneck process of wafer fabrications in the semiconductor industry,an effective estimation of distribution algorithm is proposed for scheduling problems of parallel litho machines with reticle constraints,where multiple reticles are available for each reticle type.First,the scheduling problem domain of parallel litho machines is described with reticle constraints and mathematical programming formulations are put forward with the objective of minimizing total weighted completion time.Second,estimation of distribution algorithm is developed with a decoding scheme specially designed to deal with the reticle constraints.Third,an insert-based local search with the first move strategy is introduced to enhance the local exploitation ability of the algorithm.Finally,simulation experiments and analysis demonstrate the effectiveness of the proposed algorithm.展开更多
This work aims to give a systematic construction of the two families of mixed-integer-linear-programming (MILP) formulations, which are graph-<span style="font-family:;" "=""> </span&...This work aims to give a systematic construction of the two families of mixed-integer-linear-programming (MILP) formulations, which are graph-<span style="font-family:;" "=""> </span><span style="font-family:Verdana;">based and sequence-based, of the well-known scheduling problem<img src="Edit_41010f25-7ca5-482c-89be-790fad4616e1.png" alt="" /></span><span style="font-family:Verdana;text-align:justify;">. Two upper bounds of job completion times are introduced. A numerical test result analysis is conducted with a two-fold objective 1) testing the performance of each solving methods, and 2) identifying and analyzing the tractability of an instance according to the instance structure in terms of the number of machines, of the jobs setup time lengths and of the jobs release date distribution over the scheduling horizon.</span> <div> <span style="font-family:Verdana;text-align:justify;"><br /> </span> </div>展开更多
Abstract Most papers in scheduling research have treated individual job processing times as fixed parameters. However, in many practical situations, a manager may control processing time by reallocating resources. In ...Abstract Most papers in scheduling research have treated individual job processing times as fixed parameters. However, in many practical situations, a manager may control processing time by reallocating resources. In this paper, authors consider a machine scheduling problem with controllable processing times. In the first part of this paper, a special case where the processing times and compression costs are uniform among jobs is discussed. Theoretical results are derived that aid in developing an O(n 2) algorithm to slove the problem optimally. In the second part of this paper, authors generalize the discussion to general case. An effective heuristic to the general problem will be presented.展开更多
This study focuses on the scheduling problem of unrelated parallel batch processing machines(BPM)with release times,a scenario derived from the moulding process in a foundry.In this process,a batch is initially formed...This study focuses on the scheduling problem of unrelated parallel batch processing machines(BPM)with release times,a scenario derived from the moulding process in a foundry.In this process,a batch is initially formed,placed in a sandbox,and then the sandbox is positioned on a BPM formoulding.The complexity of the scheduling problem increases due to the consideration of BPM capacity and sandbox volume.To minimize the makespan,a new cooperated imperialist competitive algorithm(CICA)is introduced.In CICA,the number of empires is not a parameter,and four empires aremaintained throughout the search process.Two types of assimilations are achieved:The strongest and weakest empires cooperate in their assimilation,while the remaining two empires,having a close normalization total cost,combine in their assimilation.A new form of imperialist competition is proposed to prevent insufficient competition,and the unique features of the problem are effectively utilized.Computational experiments are conducted across several instances,and a significant amount of experimental results show that the newstrategies of CICAare effective,indicating promising advantages for the considered BPMscheduling problems.展开更多
In this paper, a parallel machine scheduling problem was considered , where the processing time of a job is a simple linear function of its starting time. The objective is to minimize makespan. A fully polynomial time...In this paper, a parallel machine scheduling problem was considered , where the processing time of a job is a simple linear function of its starting time. The objective is to minimize makespan. A fully polynomial time approximation scheme for the problem of scheduling n deteriorating jobs on two identical machines was worked out. Furthermore, the result was generalized to the case of a fixed number of machines.展开更多
Fabric dyeing is a critical production process in the clothing industry and heavily relies on batch processing machines(BPM).In this study,the parallel BPM scheduling problem with machine eligibility in fabric dyeing ...Fabric dyeing is a critical production process in the clothing industry and heavily relies on batch processing machines(BPM).In this study,the parallel BPM scheduling problem with machine eligibility in fabric dyeing is considered,and an adaptive cooperated shuffled frog-leaping algorithm(ACSFLA)is proposed to minimize makespan and total tardiness simultaneously.ACSFLA determines the search times for each memeplex based on its quality,with more searches in high-quality memeplexes.An adaptive cooperated and diversified search mechanism is applied,dynamically adjusting search strategies for each memeplex based on their dominance relationships and quality.During the cooperated search,ACSFLA uses a segmented and dynamic targeted search approach,while in non-cooperated scenarios,the search focuses on local search around superior solutions to improve efficiency.Furthermore,ACSFLA employs adaptive population division and partial population shuffling strategies.Through these strategies,memeplexes with low evolutionary potential are selected for reconstruction in the next generation,while thosewithhighevolutionarypotential are retained to continue their evolution.Toevaluate the performance of ACSFLA,comparative experiments were conducted using ACSFLA,SFLA,ASFLA,MOABC,and NSGA-CC in 90 instances.The computational results reveal that ACSFLA outperforms the other algorithms in 78 of the 90 test cases,highlighting its advantages in solving the parallel BPM scheduling problem with machine eligibility.展开更多
As a complicated optimization problem,parallel batch processing machines scheduling problem(PBPMSP)exists in many real-life manufacturing industries such as textiles and semiconductors.Machine eligibility means that a...As a complicated optimization problem,parallel batch processing machines scheduling problem(PBPMSP)exists in many real-life manufacturing industries such as textiles and semiconductors.Machine eligibility means that at least one machine is not eligible for at least one job.PBPMSP and scheduling problems with machine eligibility are frequently considered;however,PBPMSP with machine eligibility is seldom explored.This study investigates PBPMSP with machine eligibility in fabric dyeing and presents a novel shuffled frog-leaping algorithm with competition(CSFLA)to minimize makespan.In CSFLA,the initial population is produced in a heuristic and random way,and the competitive search of memeplexes comprises two phases.Competition between any two memeplexes is done in the first phase,then iteration times are adjusted based on competition,and search strategies are adjusted adaptively based on the evolution quality of memeplexes in the second phase.An adaptive population shuffling is given.Computational experiments are conducted on 100 instances.The computational results showed that the new strategies of CSFLA are effective and that CSFLA has promising advantages in solving the considered PBPMSP.展开更多
This work is aimed at investigating the online scheduling problem on two parallel and identical machines with a new feature that service requests from various customers are entitled to many different grade of service ...This work is aimed at investigating the online scheduling problem on two parallel and identical machines with a new feature that service requests from various customers are entitled to many different grade of service (GoS) levels, so each job and machine are labelled with the GoS levels, and each job can be processed by a particular machine only when its GoS level is no less than that of the machine. The goal is to minimize the makespan. For non-preemptive version, we propose an optimal online al-gorithm with competitive ratio 5/3. For preemptive version, we propose an optimal online algorithm with competitive ratio 3/2.展开更多
The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this wor...The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.展开更多
In this paper we investigate a variant of the scheduling problem on two uniform machines with speeds 1 and s. For this problem, we are given two potential uniform machines to process a sequence of independent jobs. Ma...In this paper we investigate a variant of the scheduling problem on two uniform machines with speeds 1 and s. For this problem, we are given two potential uniform machines to process a sequence of independent jobs. Machines need to be activated before starting to process, and each machine activated incurs a fixed machine activation cost. No machines are initially activated, and when a job is revealed, the algorithm has the option to activate new machines. The objective is to minimize the sum of the makespan and the machine activation cost. We design optimal online algorithms with competitive ratio of (2s+1)/(s+1) for every s≥1.展开更多
This paper considers parallel machine scheduling with special jobs. Normal jobs can be processed on any of the parallel machines, while the special jobs can only be processed on one machine. The problem is analyzed fo...This paper considers parallel machine scheduling with special jobs. Normal jobs can be processed on any of the parallel machines, while the special jobs can only be processed on one machine. The problem is analyzed for various manufacturing conditions and service requirements. The off-line scheduling problem is transformed into a classical parallel machine scheduling problem. The on-line scheduling uses the FCFS （first come, first served）, SWSC （special window for special customers）, and FFFS （first fit, first served） algorithms to satisfy the various requirements. Furthermore, this paper proves that FCFS has a competitive ratio of m, where m is the number of parallel machines, and this bound is asymptotically tight, SWSC has a competitive ratio of 2 and FFFS has a competitive ratio of 3- 2/m, and these bounds are tight.展开更多
基金supported by the National Natural Science Foundation of China (7060103570801062)
文摘A self-adaptive large neighborhood search method for scheduling n jobs on m non-identical parallel machines with mul- tiple time windows is presented. The problems＇ another feature lies in oversubscription, namely not all jobs can be scheduled within specified scheduling horizons due to the limited machine capacity. The objective is thus to maximize the overall profits of processed jobs while respecting machine constraints. A first-in- first-out heuristic is applied to find an initial solution, and then a large neighborhood search procedure is employed to relax and re- optimize cumbersome solutions. A machine learning mechanism is also introduced to converge on the most efficient neighborhoods for the problem. Extensive computational results are presented based on data from an application involving the daily observation scheduling of a fleet of earth observing satellites. The method rapidly solves most problem instances to optimal or near optimal and shows a robust performance in sensitive analysis.
文摘Focusing on the single machine scheduling problem which minimizes the total completion time in the presence of dynamic job arrivals, a rolling optimization scheduling algorithm is proposed based on the analysis of the character and structure of scheduling. An optimal scheduling strategy in collision window is presented. Performance evaluation of this algorithm is given. Simulation indicates that the proposed algorithm is better than other common heuristic algorithms on both the total performance and stability.
基金supported by the National Natural Science Foundation of China(61002011)the National High Technology Research and Development Program of China(863 Program)(2013AA013303)+1 种基金the Fundamental Research Funds for the Central Universities(2013RC1104)the Open Fund of the State Key Laboratory of Software Development Environment(SKLSDE-2009KF-2-08)
文摘In the cloud data centers,how to map virtual machines(VMs) on physical machines(PMs) to reduce the energy consumption is becoming one of the major issues,and the existing VM scheduling schemes are mostly to reduce energy consumption by optimizing the utilization of physical servers or network elements.However,the aggressive consolidation of these resources may lead to network performance degradation.In view of this,this paper proposes a two-stage VM scheduling scheme:(1) We propose a static VM placement scheme to minimize the number of activating PMs and network elements to reduce the energy consumption;(2) In the premise of minimizing the migration costs,we propose a dynamic VM migration scheme to minimize the maximum link utilization to improve the network performance.This scheme makes a tradeoff between energy efficiency and network performance.We design a new twostage heuristic algorithm for a solution,and the simulations show that our solution achieves good results.
基金Supported by the National Natural Science Foundation of China(91338101,91338108,61132002,6132106)Research Fund of Tsinghua University(2011Z05117)Co-innovation Laboratory of Aerospace Broadband Network Technology
文摘The scheduling efficiency of the tracking and data relay satellite system（TDRSS）is strictly limited by the scheduling degrees of freedom（DoF）,including time DoF defined by jobs＇ flexible time windows and spatial DoF brought by multiple servable tracking and data relay satellites（TDRSs）.In this paper,ageneralized multiple time windows（GMTW）model is proposed to fully exploit the time and spatial DoF.Then,the improvements of service capability and job-completion probability based on the GMTW are theoretically proved.Further,an asymmetric path-relinking（APR）based heuristic job scheduling framework is presented to maximize the usage of DoF provided by the GMTW.Simulation results show that by using our proposal 11%improvement of average jobcompletion probability can be obtained.Meanwhile,the computing time of the time-to-target can be shorten to 1/9 of the GRASP.
基金Sponsored by the Basic Research Foundation of Beijing Institute of Technology (BIT-UBF-200508G4212)
文摘A method for modeling the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure is provided. For the given n jobs to be processed on m machines, it is assumed that the processing times and the due dates are nonnegative fuzzy numbers and all the weights are positive, crisp numbers. Based on credibility measure, three parallel machine scheduling problems and a goal-programming model are formulated. Feasible schedules are evaluated not only by their objective values but also by the credibility degree of satisfaction with their precedence constraints. The genetic algorithm is utilized to find the best solutions in a short period of time. An illustrative numerical example is also given. Simulation results show that the proposed models are effective, which can deal with the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure.
基金the National Natural Science Foundation of China(grant number 61573264)。
文摘Unrelated parallel machine scheduling problem(UPMSP)is a typical scheduling one and UPMSP with various reallife constraints such as additional resources has been widely studied;however,UPMSP with additional resources,maintenance,and energy-related objectives is seldom investigated.The Artificial Bee Colony(ABC)algorithm has been successfully applied to various production scheduling problems and demonstrates potential search advantages in solving UPMSP with additional resources,among other factors.In this study,an energy-efficient UPMSP with additional resources and maintenance is considered.A dynamical artificial bee colony(DABC)algorithm is presented to minimize makespan and total energy consumption simultaneously.Three heuristics are applied to produce the initial population.Employed bee swarm and onlooker bee swarm are constructed.Computing resources are shifted from the dominated solutions to non-dominated solutions in each swarm when the given condition is met.Dynamical employed bee phase is implemented by computing resource shifting and solution migration.Computing resource shifting and feedback are used to construct dynamical onlooker bee phase.Computational experiments are conducted on 300 instances from the literature and three comparative algorithms and ABC are compared after parameter settings of all algorithms are given.The computational results demonstrate that the new strategies of DABC are effective and that DABC has promising advantages in solving the considered UPMSP.
文摘It is a NP-hard problem to schedule a list of nonresumable jobs to the available intervals of an availability-constrained single machine to minimize the scheduling length. This paper transformed this scheduling problem into a variant of the variable-sized bin packing problem, put forward eight bin packing algorithms adapted from the classic one-dimensional bin packing problem and investigated their performances from both of the worst-case and the average-case scenarios. Analytical results show that the worst-case performance ratios of the algorithms are not less than 2. Experimental results for average cases show that the Best Fit and the Best Fit Decreasing algorithm outperform any others for independent and precedence-constrained jobs respectively.
文摘The optimality of a fuzzy logic alternative to the usual treatment of uncertainties in a scheduling system using fuzzy numbers is examined formally. Processing times and due dates are fuzzified and presented by fuzzy numbers. With introducing the necessity measure, we compare fuzzy completion times of jobs with fuzzy due dates to decide whether jobs are tardy. The object is to minimize the numbers of tardy jobs. The efficient solution method for this problem is proposed. And deterministic counterpart of this single machine scheduling problem is a special case of fuzzy version.
基金Supported by the National High Technology Research and Development Programme of China(No.2009AA043000)the National Natural Science Foundation of China(No.61273035,71471135)
文摘In order to improve the scheduling efficiency of photolithography,bottleneck process of wafer fabrications in the semiconductor industry,an effective estimation of distribution algorithm is proposed for scheduling problems of parallel litho machines with reticle constraints,where multiple reticles are available for each reticle type.First,the scheduling problem domain of parallel litho machines is described with reticle constraints and mathematical programming formulations are put forward with the objective of minimizing total weighted completion time.Second,estimation of distribution algorithm is developed with a decoding scheme specially designed to deal with the reticle constraints.Third,an insert-based local search with the first move strategy is introduced to enhance the local exploitation ability of the algorithm.Finally,simulation experiments and analysis demonstrate the effectiveness of the proposed algorithm.
文摘This work aims to give a systematic construction of the two families of mixed-integer-linear-programming (MILP) formulations, which are graph-<span style="font-family:;" "=""> </span><span style="font-family:Verdana;">based and sequence-based, of the well-known scheduling problem<img src="Edit_41010f25-7ca5-482c-89be-790fad4616e1.png" alt="" /></span><span style="font-family:Verdana;text-align:justify;">. Two upper bounds of job completion times are introduced. A numerical test result analysis is conducted with a two-fold objective 1) testing the performance of each solving methods, and 2) identifying and analyzing the tractability of an instance according to the instance structure in terms of the number of machines, of the jobs setup time lengths and of the jobs release date distribution over the scheduling horizon.</span> <div> <span style="font-family:Verdana;text-align:justify;"><br /> </span> </div>
文摘Abstract Most papers in scheduling research have treated individual job processing times as fixed parameters. However, in many practical situations, a manager may control processing time by reallocating resources. In this paper, authors consider a machine scheduling problem with controllable processing times. In the first part of this paper, a special case where the processing times and compression costs are uniform among jobs is discussed. Theoretical results are derived that aid in developing an O(n 2) algorithm to slove the problem optimally. In the second part of this paper, authors generalize the discussion to general case. An effective heuristic to the general problem will be presented.
基金the National Natural Science Foundation of China(Grant Number 61573264).
文摘This study focuses on the scheduling problem of unrelated parallel batch processing machines(BPM)with release times,a scenario derived from the moulding process in a foundry.In this process,a batch is initially formed,placed in a sandbox,and then the sandbox is positioned on a BPM formoulding.The complexity of the scheduling problem increases due to the consideration of BPM capacity and sandbox volume.To minimize the makespan,a new cooperated imperialist competitive algorithm(CICA)is introduced.In CICA,the number of empires is not a parameter,and four empires aremaintained throughout the search process.Two types of assimilations are achieved:The strongest and weakest empires cooperate in their assimilation,while the remaining two empires,having a close normalization total cost,combine in their assimilation.A new form of imperialist competition is proposed to prevent insufficient competition,and the unique features of the problem are effectively utilized.Computational experiments are conducted across several instances,and a significant amount of experimental results show that the newstrategies of CICAare effective,indicating promising advantages for the considered BPMscheduling problems.
基金supported by the National Natural Science Foundation of China （Grant No.10101010）
文摘In this paper, a parallel machine scheduling problem was considered , where the processing time of a job is a simple linear function of its starting time. The objective is to minimize makespan. A fully polynomial time approximation scheme for the problem of scheduling n deteriorating jobs on two identical machines was worked out. Furthermore, the result was generalized to the case of a fixed number of machines.
文摘Fabric dyeing is a critical production process in the clothing industry and heavily relies on batch processing machines(BPM).In this study,the parallel BPM scheduling problem with machine eligibility in fabric dyeing is considered,and an adaptive cooperated shuffled frog-leaping algorithm(ACSFLA)is proposed to minimize makespan and total tardiness simultaneously.ACSFLA determines the search times for each memeplex based on its quality,with more searches in high-quality memeplexes.An adaptive cooperated and diversified search mechanism is applied,dynamically adjusting search strategies for each memeplex based on their dominance relationships and quality.During the cooperated search,ACSFLA uses a segmented and dynamic targeted search approach,while in non-cooperated scenarios,the search focuses on local search around superior solutions to improve efficiency.Furthermore,ACSFLA employs adaptive population division and partial population shuffling strategies.Through these strategies,memeplexes with low evolutionary potential are selected for reconstruction in the next generation,while thosewithhighevolutionarypotential are retained to continue their evolution.Toevaluate the performance of ACSFLA,comparative experiments were conducted using ACSFLA,SFLA,ASFLA,MOABC,and NSGA-CC in 90 instances.The computational results reveal that ACSFLA outperforms the other algorithms in 78 of the 90 test cases,highlighting its advantages in solving the parallel BPM scheduling problem with machine eligibility.
基金supported by the National Natural Science Foundation of China(Grant Number 61573264).
文摘As a complicated optimization problem,parallel batch processing machines scheduling problem(PBPMSP)exists in many real-life manufacturing industries such as textiles and semiconductors.Machine eligibility means that at least one machine is not eligible for at least one job.PBPMSP and scheduling problems with machine eligibility are frequently considered;however,PBPMSP with machine eligibility is seldom explored.This study investigates PBPMSP with machine eligibility in fabric dyeing and presents a novel shuffled frog-leaping algorithm with competition(CSFLA)to minimize makespan.In CSFLA,the initial population is produced in a heuristic and random way,and the competitive search of memeplexes comprises two phases.Competition between any two memeplexes is done in the first phase,then iteration times are adjusted based on competition,and search strategies are adjusted adaptively based on the evolution quality of memeplexes in the second phase.An adaptive population shuffling is given.Computational experiments are conducted on 100 instances.The computational results showed that the new strategies of CSFLA are effective and that CSFLA has promising advantages in solving the considered PBPMSP.
基金Project supported by the National Natural Science Foundation of China (No. 10271110) and the Teaching and Research Award Pro-gram for Outstanding Young Teachers in Higher Education, Institu-tions of MOE, China
文摘This work is aimed at investigating the online scheduling problem on two parallel and identical machines with a new feature that service requests from various customers are entitled to many different grade of service (GoS) levels, so each job and machine are labelled with the GoS levels, and each job can be processed by a particular machine only when its GoS level is no less than that of the machine. The goal is to minimize the makespan. For non-preemptive version, we propose an optimal online al-gorithm with competitive ratio 5/3. For preemptive version, we propose an optimal online algorithm with competitive ratio 3/2.
基金Projects(61573144,61773165,61673175,61174040)supported by the National Natural Science Foundation of ChinaProject(222201717006)supported by the Fundamental Research Funds for the Central Universities,China
文摘The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.
基金Project (No. Y605316) supported by the Natural Science Foundationof Zhejiang Province, China and the Natural Science Foundation of the Education Department of Zhejiang Province (No. 20060578), China
文摘In this paper we investigate a variant of the scheduling problem on two uniform machines with speeds 1 and s. For this problem, we are given two potential uniform machines to process a sequence of independent jobs. Machines need to be activated before starting to process, and each machine activated incurs a fixed machine activation cost. No machines are initially activated, and when a job is revealed, the algorithm has the option to activate new machines. The objective is to minimize the sum of the makespan and the machine activation cost. We design optimal online algorithms with competitive ratio of (2s+1)/(s+1) for every s≥1.
基金Supported by the National Natural Science Foundation of China (No.70471008)
文摘This paper considers parallel machine scheduling with special jobs. Normal jobs can be processed on any of the parallel machines, while the special jobs can only be processed on one machine. The problem is analyzed for various manufacturing conditions and service requirements. The off-line scheduling problem is transformed into a classical parallel machine scheduling problem. The on-line scheduling uses the FCFS （first come, first served）, SWSC （special window for special customers）, and FFFS （first fit, first served） algorithms to satisfy the various requirements. Furthermore, this paper proves that FCFS has a competitive ratio of m, where m is the number of parallel machines, and this bound is asymptotically tight, SWSC has a competitive ratio of 2 and FFFS has a competitive ratio of 3- 2/m, and these bounds are tight.
