A multi-objective DCP model for bi-level resource-constrained project scheduling problems in grounding grid system project under hybrid uncertainty

Zhang, Zhe; Liu, Ming; Zhou, Xiaoyang; Chen, Lu

doi:10.1007/s12205-015-0615-6

Cited by 7 publications

(2 citation statements)

References 37 publications

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“…In this article, the project owner seeks to maximize profits whereas the contractor attempts to minimize cost. Finally, PSO was utilized by Zhang to solve the RCPSP with multiple objectives or multiple modes, where the contractor is the Upper Level Decision Maker and the outsourcing partner is the Lower Level Decision Maker (Zhang, 2014;Zhang, Liu, Zhou & Chen, 2015;Zhang & Xu, 2015).…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

The project scheduling problem with non-deterministic activities duration: A literature review

Pimiento

Serna

2018

JIEM

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Abstract:Purpose: The goal of this article is to provide an extensive literature review of the models and solution procedures proposed by many researchers interested on the Project Scheduling Problem with nondeterministic activities duration.Design/methodology/approach: This paper presents an exhaustive literature review, identifying the existing models where the activities duration were taken as uncertain or random parameters. In order to get published articles since 1996, was employed the Scopus database. The articles were selected on the basis of reviews of abstracts, methodologies, and conclusions. The results were classified according to following characteristics: year of publication, mathematical representation of the activities duration, solution techniques applied, and type of problem solved.Findings: Genetic Algorithms (GA) was pointed out as the main solution technique employed by researchers, and the Resource-Constrained Project Scheduling Problem (RCPSP) as the most studied type of problem. On the other hand, the application of new solution techniques, and the possibility of incorporating traditional methods into new PSP variants was presented as research trends.Originality/value: This literature review contents not only a descriptive analysis of the published articles but also a statistical information section in order to examine the state of the research activity carried out in relation to the Project Scheduling Problem with non-deterministic activities duration.

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Section: Particle Swarm Optimizationmentioning

confidence: 99%

The project scheduling problem with non-deterministic activities duration: A literature review

Pimiento

Serna

2018

JIEM

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“…He firstly proposed the DCP in stochastic environments [12], and then, he gave the theoretical frameworks of DCP in fuzzy environments [11,13], random fuzzy DCP [14], and fuzzy random DCP [9]. In the past few years, DCP has been used to solve many optimization problems, such as the dynamic facility layout problem [15], the bi-level resourceconstrained project scheduling problems [16], and the inventory modeling problems without and with backordering [17].…”

Section: Introductionmentioning

confidence: 99%

Dependent-Chance Programming on Sugeno Measure Space

Hong

Song

2017

J. Uncertain. Anal. Appl.

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In order to solve the optimization problem of selecting the decision with maximal chance to meet the Sugeno event in Sugeno environment, dependent-chance programming on Sugeno measure space is proposed, which can be considered as a generalized extension of the stochastic dependent-chance programming. Firstly, the theoretical framework of dependent-chance programming on Sugeno measure space is established. Secondly, a Sugeno simulation-based hybrid approach, which consists of back propagation neural network and genetic algorithm, is presented to construct an approximate solution of the complex dependent-chance programming models on Sugeno measure space. Finally, some numerical examples are given to illustrate the effectiveness of the approach.

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