A discrete Water Wave Optimization algorithm for no-wait flow shop scheduling problem

Zhao, Fuqing; Liu, Huan; Zhang, Yi; Ma, Weimin; Zhang, Chuck

doi:10.1016/j.eswa.2017.09.028

Cited by 106 publications

(45 citation statements)

References 42 publications

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“…Furthermore, it has comparable performance with some efficient algorithms in solving NWFSSP. In addition, Zhao et al [20] proposed a discrete Water Wave Optimization (DWWO) algorithm to solve the same problem with minimization of makespan. Gao et al [21] developed an effective heuristic algorithm in which two constructive heuristics and four composite heuristics are presented for the total flow time criterion.…”

Section: Introductionmentioning

confidence: 99%

An Improved Discrete Migrating Birds Optimization Algorithm for the No-Wait Flow Shop Scheduling Problem

Zhang

Zhou

2020

IEEE Access

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An improved discrete migrating birds optimization (IDMBO) algorithm is presented in this work to solve the no-wait flow shop scheduling problem (NWFSSP) with makespan criterion. In the algorithm, all of the solutions in population are treated as birds aligned in a V formation named the leader and followers. To guarantee the quality and the diversity of initial population, the leader is provided by the standard deviation heuristic (SDH) algorithm, and the rest (the followers) are generated randomly. Given that IDMBO is a neighborhood-based search algorithm, the quality of algorithm depends heavily on the neighborhood structures, where the two variants of the hybrid multi-neighborhood strategy, which are multiply neighborhood structures embedded in variable neighborhood search (VNS) in different forms, are performed to generate the neighborhood solutions for leader and followers, respectively. Furthermore, the population reset mechanism is performed after a given number iterations without improving the current solution. The local search (LS) method can further ameliorate the quality of solutions. The computational study is conducted to analyze the efficiency of IDMBO algorithm on benchmarks designed by Reeve and Taillard. And the comparison results are shown that the presented algorithm is superior to several existing algorithms for NWFFSP. INDEX TERMS Improved discrete migrating birds optimization algorithm, no-wait flow shop scheduling problem, hybrid multi-neighborhood strategy, population reset mechanism.

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Section: Introductionmentioning

confidence: 99%

An Improved Discrete Migrating Birds Optimization Algorithm for the No-Wait Flow Shop Scheduling Problem

Zhang

Zhou

2020

IEEE Access

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“…Other nature-inspired metaheuristics are applied for solving flow shop scheduling problem, the artificial bee colony algorithm [19][20][21], ant colony optimization algorithm [22,23], and water wave optimization algorithm [24,25]. e efficiency of these metaheuristics is observed during the resolutions of the flow shop scheduling problems with several jobs and machines.…”

Section: Introductionmentioning

confidence: 99%

Solving Permutation Flow Shop Scheduling Problem with Sequence-Independent Setup Time

Belabid

Aqil

Allali

2020

Journal of Applied Mathematics

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In this paper, we study the resolution of a permutation flow shop problem with sequence-independent setup time. The objective is to minimize the maximum of job completion time, also called the makespan. In this contribution, we propose three methods of resolution, a mixed-integer linear programming (MILP) model; two heuristics, the first based on Johnson’s rule and the second based on the NEH algorithm; and finally two metaheuristics, the iterative local search algorithm and the iterated greedy algorithm. A set of test problems is simulated numerically to validate the effectiveness of our resolution approaches. For relatively small-size problems, it has been revealed that the adapted NEH heuristic has the best performance than that of the Johnson-based heuristic. For the relatively medium and large problems, the comparative study between the two metaheuristics based on the exploration of the neighborhood shows that the iterated greedy algorithm records the best performances.

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“…Given the importance of scheduling in the design of decision support systems [4], case-specific formulations, and effective solution algorithms are of high significance to help modernize the production systems. Recent studies developed state-of-the-art solution approaches [5][6][7][8][9] to facilitate the industry-scale application of the NWSPs, which are rather complex. Many other studies extended the NWSP, for example through including setup times [10], machine maintenance [11], no-idle-time situation [12], and distributed production environment [13], among the other examples (see [14]), to address case-specific industrial needs.…”

Section: Introductionmentioning

confidence: 99%

Improved Beam Search for Optimizing No-Wait Flowshops With Release Times

et al. 2020

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Production management of perishable goods is highly complex and requires well-informed decisions in corresponding stages. In such production environments, scheduling problems with time constraints are of high relevance to ensure the timely flow of the work-in-process material and goods. This study introduces the no-wait flowshop scheduling problem with release times (NWFSP-RT) to help advance decision support systems in the food production industry. For this purpose, an original mixed-integer linear programming (MILP) formulation is proposed for minimizing the makespan. Since Beam Search (BS) algorithm has been successfully applied to solve various scheduling problems, a BS algorithm, and an improved variant, the local search-based Beam Search (BSLS) algorithms are developed to solve the NWFSP-RT problem. Extensive numerical analysis is conducted to analyze the performance of the algorithms in solving this highly intractable extension of the scheduling problems. We showed that BSLS effectively avoids early convergence and local optimality while dismissing non-promising search directions within a partial enumeration solution approach. The statistical analysis confirmed that the improved BS algorithm performs better in terms of solution quality. Applications of the developed heuristic are worthwhile research topics to pursue in solving other complex optimization problems. INDEX TERMS Flowshop scheduling, no-wait, release time, Beam Search.

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A discrete Water Wave Optimization algorithm for no-wait flow shop scheduling problem

Cited by 106 publications

References 42 publications

An Improved Discrete Migrating Birds Optimization Algorithm for the No-Wait Flow Shop Scheduling Problem

An Improved Discrete Migrating Birds Optimization Algorithm for the No-Wait Flow Shop Scheduling Problem

Solving Permutation Flow Shop Scheduling Problem with Sequence-Independent Setup Time

Improved Beam Search for Optimizing No-Wait Flowshops With Release Times

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