Parallel machine scheduling to maximize the weighted number of just-in-time jobs

Adamu, Muminu O.; Abass, O

doi:10.4314/jast.v15i1-2.54819

Cited by 8 publications

(18 citation statements)

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“…This work seeks to improve the performance of the underlying meta-heuristics (GA, PSO, and SA) by potentially hybridising them with some features of the greedy heuristic proposed by Adamu and Abass [25]. The key feature of the greedy heuristics in that work essentially lies in the order in which jobs were assigned to machines.…”

Section: Greedy Hybridsmentioning

confidence: 99%

“…Adamu and Abass [25] proposed four greedy heuristics that attempt to provide near-optimal solutions to the parallel machine scheduling problem. In this paper, the fourth heuristic (DO2) is used.…”

Section: Greedy Heuristicmentioning

confidence: 99%

“…The key feature of the greedy heuristics in that work essentially lies in the order in which jobs were assigned to machines. So the mechanisms of ordering in DO2 [25] are incorporated in the meta-heuristics (GA, PSO, SA).…”

Section: Greedy Hybridsmentioning

confidence: 99%

“…The heuristics were tested on problems generated with 100, 200, 300, and 400 jobs, similar to Adamu and Abass [25], Adamu and Adewumi [26], Ho and Chang [5], Baptiste et al [14], and M'Hallah and Bulfin [12]. The number of machines was set at levels of 2, 5, 10, 15, and 20.…”

Section: Data Generationmentioning

confidence: 99%

“…They also considered a special case with agreeable earliness and tardiness weights where they gave on O(n 3 ) complexity (Pm|p j = 1, r j , agreeable ET weights|∑w j (U j + V j )). Adamu and Abass [25] proposed four greedy heuristics for the Pm||∑w j (U j + V j ) problem, and performed extensive computational experiments. Adamu and Adewumi [26] proposed some metaheuristics and their hybrids to solve the problem considered by Adamu and Abass [25]; they found them performing better.…”

Section: Introductionmentioning

confidence: 99%

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Comparing the Performance of Different Meta-Heuristics for Unweighted Parallel Machine Scheduling

Adamu

Adewumi

2015

sajie

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This article considers the due window scheduling problem to minimise the number of early and tardy jobs on identical parallel machines. This problem is known to be NP complete and thus finding an optimal solution is unlikely. Three meta-heuristics and their hybrids are proposed and extensive computational experiments are conducted. The purpose of this paper is to compare the performance of these meta-heuristics and their hybrids and to determine the best among them. Detailed comparative tests have also been conducted to analyse the different heuristics with the simulated annealing hybrid giving the best result. OPSOMMINGDie minimering van vroeë en trae take op identiese parallelle masjien met behulp van die gepaste gleufskeduleringsprobleem word oorweeg. Die probleem is nie-deterministies polinomiese tyd volledig en die vind van 'n optimale oplossing is dus onwaarskynlik. Drie meta-heuristieke en hul hibriede word voorgestel en uitgebreide berekeningseksperimente word uitgevoer. Die doel van hierdie artikel is om die vertoning van hierdie metaheuristieke en hul hibriede met mekaar te vergelyk om sodoende die beste te identifiseer. Gedetaileerde vergelykende toetse is ook uitgevoer om die verskillende heuristieke te ondersoek; daar is gevind dat die gesimuleerde uitgloei hibried die beste resultaat lewer.

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Section: Greedy Hybridsmentioning

confidence: 99%

Section: Greedy Heuristicmentioning

confidence: 99%

Section: Greedy Hybridsmentioning

confidence: 99%

Section: Data Generationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparing the Performance of Different Meta-Heuristics for Unweighted Parallel Machine Scheduling

Adamu

Adewumi

2015

sajie

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Metaheuristics to solve a tasks scheduling problem in parallel identical machines with unavailability periods

Zitouni

Selt

2015

RAIRO-Oper. Res.

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In this paper, we introduce an approach for scheduling problems of n tasks on m identical parallel machines with unavailability periods. This problem is strongly NP-complete which makes finding an optimal solution looks impossible task. In this frame, we suggest a novel heuristic in which availability periods of each machine are filled with the highest weighted tasks. To improve the performance of this heuristic, we have used, on one hand, different diversification strategies with the aim of exploring unvisited regions of the solution space, and on the other hand, two well-known neighborhoods (neighborhood by swapping and neighborhood by insertion). The computational experiment was carried out on three identical parallel machines with different availability periods. It must be mentioned that tasks movement can be within one machine or between different machines. The performance criterion to optimize in this problem is the weighted sum of the end dates of tasks. Note that all data in this problem are integer and deterministic.

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Interval Balanced Multiprocessor Scheduling of Modular Jobs

Levin

2021

J. Commun. Technol. Electron.

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Parallel machine scheduling to maximize the weighted number of just-in-time jobs

Cited by 8 publications

References 0 publications

Comparing the Performance of Different Meta-Heuristics for Unweighted Parallel Machine Scheduling

Comparing the Performance of Different Meta-Heuristics for Unweighted Parallel Machine Scheduling

Metaheuristics to solve a tasks scheduling problem in parallel identical machines with unavailability periods

Interval Balanced Multiprocessor Scheduling of Modular Jobs

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