Comparing meta-heuristic approaches for parallel machine scheduling problems

Mendes, Alexandre; Müller, Felipe Martins; França, Paulo Morelato; Moscato, Pablo

doi:10.1080/09537280110069649

Cited by 50 publications

(18 citation statements)

References 7 publications

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“…Yi and Wang [15] proposed a tabu search (TS) algorithm for minimizing the total flow time in a parallel machines scheduling problem with sequence-independent family setup times. Mendes et al [16] addressed the parallel machine scheduling problem with sequence-dependent setup times, in which the minimization of the completion time was considered as objective function. They proposed two metaheuristic algorithms for solving this problem.…”

Section: Introductionmentioning

confidence: 99%

A vibration damping optimization algorithm for a parallel machines scheduling problem with sequence-independent family setup times

Mehdizadeh

Tavakkoli–Moghaddam

Yazdani

2015

Applied Mathematical Modelling

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Parallel machines scheduling problem is a branch of production scheduling, which is among the most difficult combinatorial optimization problems. This paper develops a meta-heuristic algorithm based on the concept of the vibration damping in mechanical vibration, called vibration damping optimization (VDO) algorithm for optimizing the identical parallel machine scheduling problem with sequence-independent family setup times. The objective function of this problem is to minimize the total weighted completion time. Furthermore, the Taguchi experimental design method is applied to set and estimate the appropriate values of the parameters required in our proposed VDO. We computationally compare the results obtained by the proposed VDO with the results of the genetic algorithm (GA) and branch-and-bound method. Consequently, the computational results validate the quality of the proposed algorithm.

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Section: Introductionmentioning

confidence: 99%

A vibration damping optimization algorithm for a parallel machines scheduling problem with sequence-independent family setup times

Mehdizadeh

Tavakkoli–Moghaddam

Yazdani

2015

Applied Mathematical Modelling

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“…They propose a genetic algorithm to solve this problem. Mendes et al [14] consider a parallel machines scheduling problem. The authors propose a taboo search and memetic approach based local search procedures to solve this problem.…”

Section: Literature Reviewmentioning

confidence: 99%

“…It consists to make the link between the variable Yipt and the starting time of job processing in position p. Constraint (14) illustrates the total completion time. Constraint (15) and constraint (16) are binary variables.…”

Section: Problem Formulationmentioning

confidence: 99%

Investigations on Genetic Algorithm Performances in a Parallel Machines Scheduling Environment

Belkaid¹,

Yalaoui²,

Sari³

2017

Open Autom. Control Syst. J.

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Abstract:Objective:The objective is to propose a resolution method to solve the identical parallel machines scheduling problem with non-renewable resources in manufacturing environment to minimize the total completion time. Introduction:Since the consideration of consumable resources becomes one of the strategic competitive tools to ensure companies performance and the stability of their production systems. This study considers a parallel machines scheduling problem with non-renewable resources. Materials and Methods:TA mathematical model is developed in order to find an optimal solution. Due to the problem complexity and prohibitive computational time to obtain an exact solution, a genetic algorithm is proposed and several heuristics are adapted to minimize the total completion time. Results:The simulation results show that the proposed genetic algorithm gives the same results as the mathematical model for small instances (exact solution) and performs the best compared to heuristics for medium and large instances. Conclusion:The scheduling problem in parallel machine environment with consumables resources is studied in this paper. A mathematical model and a metaheuristic are proposed to solve it in order to minimize the total completion time. The simulation results demonstrate the effectiveness of the proposed metaheuristic.

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“…Hübscher and Glover [18] proposed a tabu search algorithm, FatemiGhomi and Jolai-Ghazvini [7] a local search approach based on 2-exchanges. Mendes et al [23] compared a tabu search approach with a memetic algorithm, while Frangioni, Necciari and Scutellà [8] presented a local search algorithm based on multiple exchanges within large neighborhoods.…”

Section: Heuristic Algorithmsmentioning

confidence: 99%

Lower bounds and heuristic algorithms for the ki-partitioning problem

Dell’Amico

Iori

Martello

et al. 2006

European Journal of Operational Research

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We consider the problem of partitioning a set of positive integers values into a given number of subsets, each having an associated cardinality limit, so that the maximum sum of values in a subset is minimized, and the number of values in each subset does not exceed the corresponding limit. The problem is related to scheduling and bin packing problems. We give combinatorial lower bounds, reduction criteria, constructive heuristics, a scatter search approach, and a lower bound based on column generation. The outcome of extensive computational experiments is presented.

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Comparing meta-heuristic approaches for parallel machine scheduling problems

Cited by 50 publications

References 7 publications

A vibration damping optimization algorithm for a parallel machines scheduling problem with sequence-independent family setup times

A vibration damping optimization algorithm for a parallel machines scheduling problem with sequence-independent family setup times

Investigations on Genetic Algorithm Performances in a Parallel Machines Scheduling Environment

Lower bounds and heuristic algorithms for the ki-partitioning problem

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