Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs

Cheng, Wenming; Guo, Peng; Zhang, Zeqiang; Zeng, Ming; Liang, Jing

doi:10.1155/2012/928312

Cited by 28 publications

(49 citation statements)

References 64 publications

(20 reference statements)

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“…Thus the RIVH values of the test instances with H 2 are less than that of the instances with H 1 and H 3 . This observation has been demonstrated by Cheng et al [8] for parallel machine scheduling problem. In this case, the heuristic CA PS can give more optimal solutions compared with the instances with H 1 and H 3 .…”

Section: Resultssupporting

confidence: 58%

Scheduling step-deteriorating jobs to minimise the total weighted tardiness on a single machine

Guo

Wang

2015

International Journal of Systems Science: Operations & Logi

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This paper addresses the scheduling problem of minimizing the total weighted tardiness on a single machine with step-deteriorating jobs. With the assumption of deterioration, the job processing times are modeled by step functions of job starting times and pre-specified job deteriorating dates. The introduction of step-deteriorating jobs makes a single machine total weighted tardiness problem more intractable. The computational complexity of this problem under consideration was not determined. In this study, it is firstly proved to be strongly NP-hard. Then a mixed integer programming model is derived for solving the problem instances optimally. In order to tackle large-sized problems, seven dispatching heuristic procedures are developed for near-optimal solutions. Meanwhile, the solutions delivered by the proposed heuristic are further improved by a pair-wise swap movement. Computational results are presented to reveal the performance of all proposed approaches.

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Section: Resultssupporting

confidence: 58%

Scheduling step-deteriorating jobs to minimise the total weighted tardiness on a single machine

Guo

Wang

2015

International Journal of Systems Science: Operations & Logi

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“…Therefore, our article seems to be the first study of this problem. In order to evaluate the effectiveness of the proposed algorithm, the performance of the HDCS is compared with the discrete cuckoo search algorithm without local search strategy (DCS) and the variable neighborhood search proposed by Cheng et al (2012) for each test instance, where Alg sol is the objective function value obtained for a given algorithm and M in sol is the best solution of all experiments for each test problem.…”

Section: Computational Experimentsmentioning

confidence: 99%

Parallel machine scheduling with step-deteriorating jobs and setup times by a hybrid discrete cuckoo search algorithm

Guo

Cheng

Wang

2015

Engineering Optimization

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This article considers the parallel machine scheduling problem with step-deteriorating jobs and sequence-dependent setup times. The objective is to minimize the total tardiness by determining the allocation and sequence of jobs on identical parallel machines. In this problem, the processing time of each job is a step function dependent upon its starting time. An individual extended time is penalized when the starting time of a job is later than a specific deterioration date. The possibility of deterioration of a job makes the parallel machine scheduling problem more challenging than ordinary ones. A mixed integer programming model for the optimal solution is derived. Due to its NP-hard nature, a hybrid discrete cuckoo search algorithm is proposed to solve this problem. In order to generate a good initial swarm, a modified heuristic named the MBHG is incorporated into the initialization of population. Several discrete operators are proposed in the random walk of Lévy Flights and the crossover search. Moreover, a local search procedure based on variable neighborhood descent is integrated into the algorithm as a hybrid strategy in order to improve the quality of elite solutions. Computational experiments are executed on two sets of randomly generated test instances. The results show that the proposed hybrid algorithm can yield better solutions in comparison with the commercial solver CPLEX with one hour time limit, discrete cuckoo search algorithm and the existing variable neighborhood search algorithm.

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“…The main search mechanism of VNS is to systematically change the neighborhood among candidate neighborhoods so as to enhance the search diversity. Since proposed by Mladenović and Hansen [43], VNS has been successfully adopted to solve many kinds of difficult combinatorial optimization problems, especially the scheduling problems [44][45][46]. Therefore, in this paper we also adopt VNS and extend it to solve the biobjective HFS problem based on the Pareto dominance concept.…”

Section: Canonical Single Objective Vnsmentioning

confidence: 99%

A Pareto-Based Adaptive Variable Neighborhood Search for Biobjective Hybrid Flow Shop Scheduling Problem with Sequence-Dependent Setup Time

Tian

Liu

2016

Mathematical Problems in Engineering

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Different from most researches focused on the single objective hybrid flowshop scheduling (HFS) problem, this paper investigates a biobjective HFS problem with sequence dependent setup time. The two objectives are the minimization of total weighted tardiness and the total setup time. To efficiently solve this problem, a Pareto-based adaptive biobjective variable neighborhood search (PABOVNS) is developed. In the proposed PABOVNS, a solution is denoted as a sequence of all jobs and a decoding procedure is presented to obtain the corresponding complete schedule. In addition, the proposed PABOVNS has three major features that can guarantee a good balance of exploration and exploitation. First, an adaptive selection strategy of neighborhoods is proposed to automatically select the most promising neighborhood instead of the sequential selection strategy of canonical VNS. Second, a two phase multiobjective local search based on neighborhood search and path relinking is designed for each selected neighborhood. Third, an external archive with diversity maintenance is adopted to store the nondominated solutions and at the same time provide initial solutions for the local search. Computational results based on randomly generated instances show that the PABOVNS is efficient and even superior to some other powerful multiobjective algorithms in the literature.

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Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs

Cited by 28 publications

References 64 publications

Scheduling step-deteriorating jobs to minimise the total weighted tardiness on a single machine

Scheduling step-deteriorating jobs to minimise the total weighted tardiness on a single machine

Parallel machine scheduling with step-deteriorating jobs and setup times by a hybrid discrete cuckoo search algorithm

A Pareto-Based Adaptive Variable Neighborhood Search for Biobjective Hybrid Flow Shop Scheduling Problem with Sequence-Dependent Setup Time

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