Simulated Annealing Algorithm for the Weighted Unrelated Parallel Machines Problem

Cruz-Chávez, Marco Antonio; Juárez-Pérez, Fredy; Ávila-Melgar, Érika Yesenia; Martinez-Oropeza, Alina

doi:10.1109/cerma.2009.46

Cited by 7 publications

(4 citation statements)

References 11 publications

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“…The results demonstrate that the GA obtains results only a few percent worse than the optimal solutions. In [126] the authors optimise the total weighted flowtime. SA is applied to solve the considered problem and shows good efficiency in obtaining optimal results.…”

Section: B Metaheuristicsmentioning

confidence: 99%

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Heuristic and Metaheuristic Methods for the Unrelated Machines Scheduling Problem: A Survey

Đurasević,

Jakobović

2021

Preprint

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Today scheduling problems have an immense effect on various areas of human lives, be it from their application in manufacturing and production industry, transportation, or workforce allocation. The unrelated parallel machines scheduling problem (UPMSP), which is only one of the many different problem types that exist, found its application in many areas like production industries or distributed computing. Due to the complexity of the problem, heuristic and metaheuristic methods are gaining more attention for solving it. Although this problem variant did not receive much attention as other models, recent years saw the increase of research dealing with this problem. During that time, many different problem variants, solution methods, or other interesting research directions were considered. However, no study has until now tried to systematise the research in which heuristic methods are applied for the UPMSP. The goal of this study is to provide an extensive literature review on the application of heuristic and metaheuristic methods for solving the UPMSP. The research was systematised and classified into several categories to enable an easy overview of the different problem and solution variants. Additionally, current trends and possible future research directions are also shortly outlined.

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Section: B Metaheuristicsmentioning

confidence: 99%

“…None [24], [25], [26], [28], [29], [30], [32], [34], [39], [40], [41], [44], [48], [49], [55], [69], [80], [82], [86], [88], [89], [90], [91], [94], [95], [97], [99], [100], [107], [112], [126], [127], [130], [132], [134], [135], [139], [148], [150], [156], [158], [162], [165], [177], [178], [183], [185], [186], [224], [227],…”

Section: Constraints Referencesunclassified

Heuristic and Metaheuristic Methods for the Unrelated Machines Scheduling Problem: A Survey

Đurasević,

Jakobović

2021

Preprint

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“…For large scale of Rm||∑j=1NwjCj problem, the researchers still have used heuristics and/or metaheuristics to find optimal or near-optimal solutions because of the complexity of the problem. Cruz-Chávez et al (2009) model the problem as a weighted bipartite matching problem and applied a simulated annealing algorithm. Rodriguez et al (2012b) propose an artificial bee colony (ABC) algorithm for the problem by combining the exploitation capability of basic ABC and the iterated greedy constructive-destructive procedure.…”

Section: Introductionmentioning

confidence: 99%

Memetic algorithm for unrelated parallel machine scheduling problem with grey processing times

Arık

2022

JM2

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Purpose This paper aims to provide a promising memetic algorithm (MA) for an unrelated parallel machine scheduling problem with grey processing times by using a simple dispatching rule in the local search phase of the proposed MA. Design/methodology/approach This paper proposes a MA for an unrelated parallel machine scheduling problem where the objective is to minimize the sum of weighted completion times of jobs with uncertain processing times. In the optimal schedule of the problem’s single machine version with deterministic processing time, the machine has a sequence where jobs are ordered in their increasing order of weighted processing times. The author adapts this property to some of their local search mechanisms that are required to assure the local optimality of the solution generated by the proposed MA. To show the efficiency of the proposed algorithm, this study uses other local search methods in the MA within this experiment. The uncertainty of processing times is expressed with grey numbers. Findings Experimental study shows that the MA with the swap-based local search and the weighted shortest processing time (WSPT) dispatching rule outperforms other MA alternatives with swap-based and insertion-based local searches without that dispatching rule. Originality/value A promising and effective MA with the WSPT dispatching rule is designed and applied to unrelated parallel machine scheduling problems where the objective is to minimize the sum of the weighted completion times of jobs with grey processing time.

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“…This problem is formulated by Azizoglu and Kirca (1999) as a mathematical program and then the solution given to solve it use a branch-and-bound algorithm. Cruz-Chávez et al (2009) also presented a solution to this problem using a simulated annealing algorithm that solves it as a weighted bipartite matching problem. The total weighted tardiness is a measure of customer satisfaction as well as it has more or less been addressed in literature (Marmier et al, 2009a;Lee et al, 1996).…”

Section: Introductionmentioning

confidence: 99%

Scheduling a maintenance activity under skills constraints to minimize total weighted tardiness and late tasks

Hedjazi

2015

10.5267/j.ijiec

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Skill management is a key factor in improving effectiveness of industrial companies, notably their maintenance services. The problem considered in this paper concerns scheduling of maintenance tasks under resource (maintenance teams) constraints. This problem is generally known as unrelated parallel machine scheduling. We consider the problem with a both objectives of minimizing total weighted tardiness (TWT) and number of tardiness tasks. Our interest is focused particularly on solving this problem under skill constraints, which each resource has a skill level. So, we propose a new efficient heuristic to obtain an approximate solution for this NP-hard problem and demonstrate his effectiveness through computational experiments. This heuristic is designed for implementation in a static maintenance scheduling problem (with unequal release dates, processing times and resource skills), while minimizing objective functions aforementioned.

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Simulated Annealing Algorithm for the Weighted Unrelated Parallel Machines Problem

Cited by 7 publications

References 11 publications

Heuristic and Metaheuristic Methods for the Unrelated Machines Scheduling Problem: A Survey

Heuristic and Metaheuristic Methods for the Unrelated Machines Scheduling Problem: A Survey

Memetic algorithm for unrelated parallel machine scheduling problem with grey processing times

Scheduling a maintenance activity under skills constraints to minimize total weighted tardiness and late tasks

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