A Multi-Objective Project Scheduling Problem Subject to Project Reliability and Multi-Mode Activities with Time Window

In this study, the necessity of considering reliability in projects and its association with other related objectives regard-ing project's scheduling is investigated. In this regard, a mathematical model to optimize the objective functions, time and reliability is presented considering budget c...

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Vydané v:Industrial Engineering & Management Systems Ročník 20; číslo 3; s. 356 - 372
Hlavní autori: Nejad, Behnam Hosseinian, Farughi, Hiwa
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: 대한산업공학회 01.09.2021
Predmet:
산업공학
Multi-Mode Activities
Multi Objective Project Scheduling
Planning &amp
Quality &amp
Scheduling
Computational Intelligence &amp
Reliability
Optimization
ISSN:1598-7248, 2234-6473
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Popis
Shrnutí:In this study, the necessity of considering reliability in projects and its association with other related objectives regard-ing project's scheduling is investigated. In this regard, a mathematical model to optimize the objective functions, time and reliability is presented considering budget constraint, and time window for starting activities, float time and multi-mode activities following the review of the literature. Due to the great difficulty of calculations in this model, two metaheuristic algorithms, namely MOPSO and NSGAII are presented to solve the model's problem in small, average and large scale and then several numerical samples are solved in all above mentioned scales to evaluate the algorithm performance. The results of solving the model using metaheuristic algorithms are compared in small-scale with the results of accurate problem-solving carried out by GAMS optimization software. The results indicate that both metaheuristic algorithms are able to achieve acceptable responses in short time considering all three forms of reliability function. In addition, MOPSO algorithm had the most desirable performance in achieving acceptable responses in less time and NSGAII algorithm had the most desirable performance in more extensively searching the response space. KCI Citation Count: 0
ISSN:1598-7248
2234-6473
DOI:10.7232/iems.2021.20.3.356