An effective operations permutation-based discrete harmony search approach for the flexible job shop scheduling problem with makespan criterion

Gaham, Mehdi; Bouzouia, Brahim; Achour, Nouara

doi:10.1007/s10489-017-0993-1

Cited by 30 publications

(8 citation statements)

References 57 publications

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“…Results indicate the reasonable computational time for large size problems. In addition to above studies, it is worth mentioning that some excellent algorithms have been presented for solving combinatorial optimization problems such as [74][75][76][77], and some of them are specialized in the field of scheduling, for instance [78][79][80][81], and which all of them give us valuable insight to extend our algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

A multi objective volleyball premier league algorithm for green scheduling identical parallel machines with splitting jobs

Salimifard

Mohammadi

et al. 2020

Appl Intell

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Parallel machine scheduling is one of the most common studied problems in recent years, however, this classic optimization problem has to achieve two conflicting objectives, i.e. minimizing the total tardiness and minimizing the total wastes, if the scheduling is done in the context of plastic injection industry where jobs are splitting and molds are important constraints. This paper proposes a mathematical model for scheduling parallel machines with splitting jobs and resource constraints. Two minimization objectives - the total tardiness and the number of waste - are considered, simultaneously. The obtained model is a bi-objective integer linear programming model that is shown to be of NP-hard class optimization problems. In this paper, a novel Multi-Objective Volleyball Premier League (MOVPL) algorithm is presented for solving the aforementioned problem. This algorithm uses the crowding distance concept used in NSGA-II as an extension of the Volleyball Premier League (VPL) that we recently introduced. Furthermore, the results are compared with six multi-objective metaheuristic algorithms of MOPSO, NSGA-II, MOGWO, MOALO, MOEA/D, and SPEA2. Using five standard metrics and ten test problems, the performance of the Pareto-based algorithms was investigated. The results demonstrate that in general, the proposed algorithm has supremacy than the other four algorithms.

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Section: Literature Reviewmentioning

confidence: 99%

A multi objective volleyball premier league algorithm for green scheduling identical parallel machines with splitting jobs

Salimifard

Mohammadi

et al. 2020

Appl Intell

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“…In the GWO, an adaptive mutation method is designed to keep the population diversity and avoid premature convergence. Recently, Gaham et al [134] proposed an effective operations permutation based discrete harmony search approach for tackling the FJSP with makespan criterion.…”

Section: Population-based Meta-heuristicsmentioning

confidence: 99%

Review on flexible job shop scheduling

Xie

Gao

Peng

et al. 2019

IET Collaborative Intelligent Manufacturing

158

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Flexible job shop scheduling problem (FJSP) is an NP‐hard combinatorial optimisation problem, which has significant applications in the real world. Due to its complexity and significance, lots of attentions have been paid to tackle this problem. In this study, the existing solution methods for the FJSP in recent literature are classified into exact algorithms, heuristics and meta‐heuristics, which are reviewed comprehensively. Moreover, the real‐world applications of the FJSP are also introduced. Finally, the development trends of the manufacturing industry are analysed, and the future research opportunities of the FJSP are summarised in detail.

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“…The hybrid algorithm was used to solve the fuzzy FJSP. Gaham et al [18] presented an operations permutation-based discrete harmony search method. That method adopted an integration of the solution harmony with a dedicated improvisation operator.…”

Section: Literature Reviewmentioning

confidence: 99%

A Modified Iterated Greedy Algorithm for Flexible Job Shop Scheduling Problem

Aqel

Gao

2019

Chin. J. Mech. Eng.

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The flexible job shop scheduling problem (FJSP) is considered as an important problem in the modern manufacturing system. It is known to be an NP-hard problem. Most of the algorithms used in solving FJSP problem are categorized as metaheuristic methods. Some of these methods normally consume more CPU time and some other methods are more complicated which make them difficult to code and not easy to reproduce. This paper proposes a modified iterated greedy (IG) algorithm to deal with FJSP problem in order to provide a simpler metaheuristic, which is easier to code and to reproduce than some other much more complex methods. This is done by separating the classical IG into two phases. Each phase is used to solve a sub-problem of the FJSP: sequencing and routing sub-problems. A set of dispatching rules are employed in the proposed algorithm for the sequencing and machine selection in the construction phase of the solution. To evaluate the performance of proposed algorithm, some experiments including some famous FJSP benchmarks have been conducted. By compared with other algorithms, the experimental results show that the presented algorithm is competitive and able to find global optimum for most instances. The simplicity of the proposed IG provides an effective method that is also easy to apply and consumes less CPU time in solving the FJSP problem.

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An effective operations permutation-based discrete harmony search approach for the flexible job shop scheduling problem with makespan criterion

Cited by 30 publications

References 57 publications

A multi objective volleyball premier league algorithm for green scheduling identical parallel machines with splitting jobs

A multi objective volleyball premier league algorithm for green scheduling identical parallel machines with splitting jobs

Review on flexible job shop scheduling

A Modified Iterated Greedy Algorithm for Flexible Job Shop Scheduling Problem

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