An improved simulated annealing for hybrid flowshops with sequence-dependent setup and transportation times to minimize total completion time and total tardiness

Naderi, Bahman; Zandieh, M.; Balagh, A. Khaleghi Ghoshe; Roshanaei, Vahid

doi:10.1016/j.eswa.2008.09.063

Cited by 155 publications

(72 citation statements)

References 32 publications

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“…This bound was proved wrong and corrected later by [69]. Simulated annealing has been used to solve a HFS with sequence dependent setup times and transportation times between stages of an automated guided vehicle in [131].…”

Section: Metaheuristicsmentioning

confidence: 99%

The hybrid flow shop scheduling problem

Ruíz

Vázquez-Rodríguez

2010

European Journal of Operational Research

670

236

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The scheduling of flow shops with multiple parallel machines per stage, usually referred to as the Hybrid Flow Shop (HFS), is a complex combinatorial problem encountered in many real world applications. Given its importance and complexity, the HFS problem has been intensively studied. This paper presents a literature review on exact, heuristic and metaheuristic methods that have been proposed for its solution.The paper discusses several variants of the HFS problem, each in turn considering different assumptions, constraints and objective functions. Research opportunities in HFS are also discussed.

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Section: Metaheuristicsmentioning

confidence: 99%

The hybrid flow shop scheduling problem

Ruíz

Vázquez-Rodríguez

2010

European Journal of Operational Research

670

236

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“…This flexibility occurs because the machines can be used to several different operations and the products can be processed by several different machines. The problem generated by this flexibility is the considerable effort to define the production scheduling and the use of available resources over time, in order to reach certain performance criteria (Tay and Ho 2008;Zhang et al 2012;Naderi et al 2009). …”

Section: Introductionmentioning

confidence: 99%

An Adaptive Genetic Algorithm for Production Scheduling on Manufacturing Systems with Simultaneous Use of Machines and AGVs

Sanches

Rocha

Castoldi

et al. 2015

J Control Autom Electr Syst

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The problem of production scheduling of manufacturing systems involves the system modeling task and the application of a technique to solve it. This kind of scheduling is characterized by the large number of possible solutions, where several researches have been using the genetic algorithms as a search method to solve this problem, since these algorithms have the capacity of globally exploring the search space and to find good solutions quickly. This paper proposes the use of adaptive genetic algorithm to solve this kind of scheduling problem. The aim of this paper was to obtain a good production schedule considering simultaneous use of machines and automated guided vehicles that minimize the makespan with low running time. The results of this paper were validated in large scenarios and compared with other approach. These results are presented and discussed in this paper.

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“…However, noise refers to those parameters causing algorithm to deviate from its target value. Taguchi method attempts to minimize the impact of noise and find the best level of controllable parameters simultaneously on the robustness basis (Tsai et al, 2007;Naderi et al, 2009). In such conditions, it is necessary to replicate the experiments in different situations to decrease detrimental effect of noise parameters.…”

Section: Taguchi Methodsmentioning

confidence: 99%