Parallel machine scheduling with fuzzy processing times using a robust genetic algorithm and simulation

Balin, Savaş

doi:10.1016/j.ins.2011.04.010

Cited by 68 publications

(23 citation statements)

References 34 publications

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“…Thus, the MODASA has higher stability and shorter running time than others. [18,19], [20,22], [17,18] 3 1,3 [18,19], [20,22] Figure 6: Gantt chart of PCD tasks in the context of without emergencies and considering emergencies. …”

Section: Computational Resultsmentioning

confidence: 99%

“…(2) Rescheduling Procedure Event-driven, lifecycle-driven and hybrid-driven are three most frequent dynamic scheduling methods to cope with emergency [19]. Event-driven means that rescheduling is activated only when task set changes because of accidents.…”

Section: Disturbancementioning

confidence: 99%

“…Krishnamoorthy et al proposed a Lagrangean approach for solving the Personnel Task Scheduling Problem (PTSP) [14]. Besides, competent genetic algorithms [15], ant colony algorithms [16], particle swarm optimization (PSO) [17], simulation [18], simulated annealing (SA) [19] and many other algorithms and methods [20][21] were used in PCD scheduling.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multi-Objective Rescheduling Model for Product Collaborative Design Considering Disturbance

Yu¹,

Yang²,

Zhao³

et al. 2014

Int. j. simul. model.

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Disturbance is inevitable in product collaborative design (PCDSP), which has always posed a great challenge for enterprises making quick response. Thus, in the paper, a multi-objective rescheduling model and its solution algorithm are presented. Disturbance cases are analysed and dynamic scheduling procedure based on event-driven and lifecycle-driven is developed firstly. Then a multiobjective rescheduling model aiming to minimum the makespan and tardiness penalty is developed. As a solution, multi-objective dynamic adaptive scheduling algorithm (MODASA), based on bi-layer coding strategy, self-adaptive double point crossover and self-adaptive mutation, is proposed following closely. Finally, analytic results from a case of a wind turbine are used to illustrate the model and method proposed in this paper. Simulation results shows that the model and algorithm have full advantages in computing speed and precision. With the analysis, it can provide insight into ways of improving the strategic and operational decision making for enterprises.

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Section: Computational Resultsmentioning

confidence: 99%

Section: Disturbancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multi-Objective Rescheduling Model for Product Collaborative Design Considering Disturbance

Yu¹,

Yang²,

Zhao³

et al. 2014

Int. j. simul. model.

View full text Add to dashboard Cite

show abstract

“…An alternative and increasingly popular approach is to use fuzzy sets in the setting of possibility theory [16,19,66], since they provide an acceptable trade-off between expressivity and computational difficulty. There are in fact numerous research papers where uncertain durations are represented as fuzzy numbers, mostly triangular fuzzy numbers, among others, for single machine scheduling [10], [32], parallel machine scheduling [4,49], flow shop scheduling [9,31], open shop scheduling [46], job shop scheduling [18,24,35,45,52,54,55,60,71] and [41], and for flexible job shop scheduling in [40,48,64,65] to mention but a few. Indeed, the recent review of metaheuristic algorithms to solve fuzzy job shop problems in [1] highlights the relevance of this topic.…”

Section: Introductionmentioning

confidence: 99%

Benchmarks for fuzzy job shop problems

Palacios

Puente

Vela

et al. 2016

Information Sciences

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Highlights• The fuzzy job shop scheduling problem with makespan minimization is revised• We survey existing metaheuristic methods and test beds for the problem • More challenging benchmark instances with LBs and competitive results are proposed• We publish old and new test beds to facilitate reproducibility and future research 1 AbstractThe fuzzy job shop scheduling problem with makespan minimisation is a problem with a significant presence in the scientific literature. However, a common meaningful comparison base is missing for such problem. This work intends to fill the gap in this domain by reviewing existing benchmarks as well as proposing new benchmark problems. First, we shall survey the existing test beds for the fuzzy job shop, analysing whether they are sufficiently varied and, most importantly, whether there is room for improvement on these instances -an essential requirement if the instances are to be useful for the scientific community in order to compare and develop new solving strategies. In the light of this analysis, we shall propose a new family of more challenging benchmark problems and provide lower bounds for the expected makespan of each instance as well as reference makespan values obtained with a memetic algorithm from the literature. The resulting benchmark will be made available so as to facilitate experiment reproducibility and encourage research competition.

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“…One of the major dilemmas in search optimization is the difficulty of identifying equilibrium between exploitation and exploration when search processes evolve (Balin 2011;Tsai et al 2008;Fazlollahtabar et al 2012). One of the reasons is that equilibrium factors (exploitation and exploration) in search algorithms are associated with the evolution processes (Wu et al 2012).…”

Section: Introductionmentioning

confidence: 99%

An adaptable optimizer for green component design

Tsai

Chen

et al. 2014

Inf Syst E-Bus Manage

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This paper proposes an adaptive mechanism for improving the availability efficiency of green component design (GCD) process. The proposed approach incorporates a wide range of GCD strategies to increase availability of the recycled/reused/remanufactured components. We have also designed a self-adjusting mechanism to enhance the versatility and generality of a genetic algorithm (GA) to improve GCD availability efficiency. The mechanism allows refinement of the GA parameters for the selections of operators in each generation. Our research contribution includes the development of a novel mechanism for the evaluation of optimal selections of reproduction strategies, adjustment and optimization of the crossover and mutation rates in evolutions, and design of Taguchi Orthogonal Arrays with a GA optimizer. The effectiveness of the proposed algorithms has been examined in a GCD chain. From the experimental results, we can conclude that the proposed approach resulted in better reproduction optimization than the traditional ones.

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Parallel machine scheduling with fuzzy processing times using a robust genetic algorithm and simulation

Cited by 68 publications

References 34 publications

Multi-Objective Rescheduling Model for Product Collaborative Design Considering Disturbance

Multi-Objective Rescheduling Model for Product Collaborative Design Considering Disturbance

Benchmarks for fuzzy job shop problems

An adaptable optimizer for green component design

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