An effective multi-start multi-level evolutionary local search for the flexible job-shop problem

Kemmoé-Tchomté, S.; Lamy, Damien; Tchernev, Nikolay

doi:10.1016/j.engappai.2017.04.002

Cited by 22 publications

(6 citation statements)

References 39 publications

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Section: Algorithm Effectiveness Analysismentioning

confidence: 99%

“…The SFLA-uGSA is an algorithm proposed in this paper, which runs 10 times to record the optimal value and the average deviation. Five evolutionary algorithms, CCGA [26], GRASP [27], SLGA [28], PSO [29], and MSCGA [30], are selected for comparison. Table 2 shows the results of this experiment, where α represents the number of jobs, β represents the number of machines, Size represents the number of operations, LB represents the known optimal solution, and SD represents the average deviation.…”

Section: Algorithm Effectiveness Analysismentioning

confidence: 99%

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Research on Multi-Objective Flexible Job Shop Scheduling Problem with Setup and Handling Based on an Improved Shuffled Frog Leaping Algorithm

Kong,

Yang

2024

Applied Sciences

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Flexible job shop scheduling problem (FJSP), widely prevalent in many intelligent manufacturing industries, is one of the most classic problems of production scheduling and combinatorial optimization. In actual manufacturing enterprises, the setup of machines and the handling of jobs have an important impact on the scheduling plan. Furthermore, there is a trend for a cluster of machines with similar functionalities to form a work center. Considering the above constraints, a new order-driven multi-equipment work center FJSP model with setup and handling including multiple objectives encompassing the minimization of the makespan, the number of machine shutdowns, and the number of handling batches is established. An improved shuffled frog leading algorithm is designed to solve it through the optimization of the initial solution population, the improvement of evolutionary operations, and the incorporation of Pareto sorting. The algorithm also combines the speed calculation method in the gravity search algorithm to enhance the stability of the solution search. Some standard FJSP data benchmarks have been selected to evaluate the effectiveness of the algorithm, and the experimental results confirm the satisfactory performance of the proposed algorithm. Finally, a problem example is designed to demonstrate the algorithm’s capability to generate an excellent scheduling plan.

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Section: Algorithm Effectiveness Analysismentioning

confidence: 99%

Section: Algorithm Effectiveness Analysismentioning

confidence: 99%

Research on Multi-Objective Flexible Job Shop Scheduling Problem with Setup and Handling Based on an Improved Shuffled Frog Leaping Algorithm

Kong,

Yang

2024

Applied Sciences

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show abstract

“…(2017b), Kemmoé‐Tchomté et al. (2017), Allahverdi et al. (2018), Ying and Lin (2018), Fatih Tasgetiren et al.…”

Section: An Overview Of Shop Scheduling Problems Characteristicsmentioning

confidence: 99%

Shop scheduling in manufacturing environments: a review

Márquez

Ribeiro

2022

Int Trans Operational Res

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We review the literature about shop scheduling problems in manufacturing systems, revealing the concepts and methodologies that most impact the usage of scheduling theory in manufacturing environments. We focus our attention on the job shop and flow shop problems and their variants. We emphasize the interactions between the scheduling functions and manufacturing paradigms such as Industry 4.0, Computer Integrated Manufacturing, Computer‐Aided Process Planning, Advanced Planning and Scheduling, and Integrated Process Planning and Scheduling. We describe the main components and characteristics of the scheduling ecosystem, and we discuss how the scheduling interacts with the components that make it up and how it is affected by them. The metadata collected from the digital libraries on which the review was based (ScienceDirect, Scopus, and Elsevier) made it possible to characterize the historical evolution of the main concepts of the scheduling ecosystem in terms of scientific publications and research trends in the period 2000–2020.

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“…If classical local searches for the JSP and its extensions usually rely on the exploration of the critical path (Bürgy 2017; Kemmoé‐Tchomté et al. 2017), the current research work considers a larger neighborhood system that enables to reach better solutions, but at the cost of higher convergence time. In the case of the present study, a simple

swap

operator is considered.…”

Section: Scheduling Problemsmentioning

confidence: 99%

Pattern mining‐based pruning strategies in stochastic local searches for scheduling problems

Laurent

Lamy

Dalmas

et al. 2021

Int Trans Operational Res

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Scheduling problems are a subclass of combinatorial problems consisting of a set of tasks/activities/jobs to be processed by a set of resources usually to minimize a time criterion. Some optimization methods used to solve these problems are hybridized with knowledge discovery techniques to extract information during the optimization process and enhance it. However, most of these hybrid techniques are custom-designed and lack generalization. In this paper a module for knowledge extraction in Stochastic Local Searches is designed, aiming to be problem independent and plugged into optimisation methods that relies on multiple Stochastic Local Search replications. The objective is to prune parts of the search space for which the exploration is likely to lead to poor solutions. This is performed through the extraction of high-quality patterns occurring in locally optimal solutions. Benchmarked on two well-known scheduling problems, the Job-shop Problem and the Resource Constrained Project Scheduling Problem, the results show both a speed up in the convergence and the reaching of better local optima solutions.

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An effective multi-start multi-level evolutionary local search for the flexible job-shop problem

Cited by 22 publications

References 39 publications

Research on Multi-Objective Flexible Job Shop Scheduling Problem with Setup and Handling Based on an Improved Shuffled Frog Leaping Algorithm

Research on Multi-Objective Flexible Job Shop Scheduling Problem with Setup and Handling Based on an Improved Shuffled Frog Leaping Algorithm

Shop scheduling in manufacturing environments: a review

Pattern mining‐based pruning strategies in stochastic local searches for scheduling problems

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