A discrete artificial bee colony algorithm for the multi-objective flexible job-shop scheduling problem with maintenance activities

Li, Junqing; Pan, Quan-Ke; Taşgetiren, M. Fatih

doi:10.1016/j.apm.2013.07.038

Cited by 242 publications

(89 citation statements)

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“…In order to schedule jobs on parallel identical machines, the use of Time Petri Net based approach has also been investigated [26] while minimizing the makespan and balancing the load among the machines Li et al [27] used discrete multi-objective Artificial Bee Colony (ABC) to optimize makespan, the total workload of machines and the workload of the critical machine. They investigated the impact of schedules on maintenance activities.…”

Section: Literature Reviewmentioning

confidence: 99%

Hybrid Black Hole Algorithm for Bi-Criteria Job Scheduling on Parallel Machines

Jeet¹,

Dhir²,

Singh³

et al. 2016

IJISA

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Abstract-Nature-inspired algorithms are recently being appreciated for solving complex optimization and engineering problems. Black hole algorithm is one of the recent nature-inspired algorithms that have obtained inspiration from black hole theory of universe. In this paper, four formulations of multi-objective black hole algorithm have been developed by using combination of weighted objectives, use of secondary storage for managing possible solutions and use of Genetic Algorithm (GA). These formulations are further applied for scheduling jobs on parallel machines while optimizing bi-criteria namely maximum tardiness and weighted flow time. It has been empirically verified that GA based multi-objective Black Hole algorithms leads to better results as compared to their counterparts. Also the use of combination of secondary storage and GA further improves the resulting job sequence. The proposed algorithms are further compared to some of the existing algorithms, and empirically found to be better. The results have been validated by numerical illustrations and statistical tests.

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Section: Literature Reviewmentioning

confidence: 99%

Hybrid Black Hole Algorithm for Bi-Criteria Job Scheduling on Parallel Machines

Jeet¹,

Dhir²,

Singh³

et al. 2016

IJISA

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“…In some works, the features incorporated into the LSR-FJS definition are taken into account: lot streaming [2][3][4][5], limited machines availability [6][7][8][9][10][11], setup times [3,5,[12][13][14][15][16][17], and transport times [3,13,17]. However, these extensions are most often considered separately.…”

Section: Related Workmentioning

confidence: 99%

“…Sometimes, a greater number of criteria are combined [5]. The Pareto front [5,9] or linear combination [9, 10] of individual criteria are the methods commonly used in the multi-objective scheduling. The multiobjective approach has a large practical importance.…”

Section: Related Workmentioning

confidence: 99%

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Off-Line and Dynamic Production Scheduling – A Comparative Case Study

Bożek¹,

Wysocki²

2016

Management and Production Engineering Review

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Accepted: 16 February 2016 A comprehensive case study of manufacturing scheduling solutions development is given. It includes highly generalized scheduling problem as well as a few scheduling modes, methods and problem models. The considered problem combines flexible job shop structure, lot streaming with variable sublots, transport times, setup times, and machine calendars. Tabu search metaheuristic and constraint programming methods have been used for the off-line scheduling. Two dynamic scheduling methods have also been implemented, i.e., dispatching rules for the completely reactive scheduling and a multi-agent system for the predictivereactive scheduling. In these implementations three distinct models of the problem have been used, based on: graph representation, optimal constraint satisfaction, and Petri net formalism. Each of these solutions has been verified in computational experiments. The results are compared and some findings about advantages, disadvantages, and suggestions on using the solutions are formulated.

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“…algorithm (Moslehi and Mahnam, 2011); hybrid Pareto-based discrete artificial bee colony (ABC) algorithm with several local search approach (Li et al, 2011); hybrid genetic algorithm (GA) and SA (Shahasaveri-Pour and Ghasemishabankareh, 2013); and the discrete ABC algorithm with TS (Li et al, 2014). Nevertheless, few studies have considered due dates for MTO manufacturing set by important customers (Wu and Weng, 2005;Turkyilmaz and Bulkan, 2015).…”

mentioning

confidence: 99%

Balancing setup workers' load of flexible job shop scheduling using hybrid genetic algorithm with tabu search strategy

Morinaga

Nagao

Sano

2016

IJDSS

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This paper describes optimisation of a multi-objective flexible job shop scheduling problem (MO-FJSP) in small and medium-sized enterprises (SMEs) where widely various products are manufactured in make-to-order (MTO) mode. A genetic algorithm using tabu search strategy was applied to solve the MO-FJSP incorporating weighted tardiness, setup worker load balance, and work-in-process. From experiments using data based on real-world SME, the solutions obtained using the proposed method are compared with those obtained by conventional earliest due date (EDD), and GA using multi-island. The results confirmed the effectiveness of the proposed method. Results imply that the proposed approach is applicable not only for production scheduling but also for estimating the investment of resources such as machine and worker capacity.Keywords: flexible job shop scheduling problem; setup workers' workload balance; work-in-process inventory; tabu search; genetic algorithm.Reference to this paper should be made as follows: Morinaga, Y., Nagao, M. and Sano, M. (2016) 'Balancing setup workers' load of flexible job shop scheduling using hybrid genetic algorithm with tabu search strategy', Int.

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A discrete artificial bee colony algorithm for the multi-objective flexible job-shop scheduling problem with maintenance activities

Cited by 242 publications

References 40 publications

Hybrid Black Hole Algorithm for Bi-Criteria Job Scheduling on Parallel Machines

Hybrid Black Hole Algorithm for Bi-Criteria Job Scheduling on Parallel Machines

Off-Line and Dynamic Production Scheduling – A Comparative Case Study

Balancing setup workers' load of flexible job shop scheduling using hybrid genetic algorithm with tabu search strategy

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