多模式、多地点资源受限项目调度问题的双目标优化

IF 1.8 Q3 MANAGEMENT Journal of Modelling in Management Pub Date : 2024-01-18 DOI:10.1108/jm2-06-2023-0123
Shiba Hessami, Hamed Davari-Ardakani, Youness Javid, Mariam Ameli
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引用次数: 0

摘要

目的 本研究旨在处理多模式资源受限项目调度问题(MRCPSP),该问题具有在多个站点之间运输资源的能力,旨在同时使项目的总完成时间和总成本最小化。所有活动通过完成-开始优先关系相互关联,不允许抢先。然后,使用ɛ-约束优化方法解决了 24 个不同大小的实例,从 5 个活动到 120 个活动不等,并报告了时间跨度、总成本和 CPU 时间。对一些实例确定了一组帕累托最优解,并进行了敏感性分析,以找出改变参数对目标值的影响。原创性/价值提出了一个新颖的双目标优化模型来处理多站点 MRCPSP,同时考虑了多站点之间资源运输的成本和时间。据作者所知,项目调度领域的研究尚未涉及这一问题。
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Bi-objective optimization of a multi-mode, multi-site resource-constrained project scheduling problem

Purpose

This study aims to deal with the multi-mode resource-constrained project scheduling problem (MRCPSP) with the ability to transport resources among multiple sites, aiming to minimize the total completion time and the total cost of the project simultaneously.

Design/methodology/approach

To deal with the problem under consideration, a bi-objective optimization model is developed. All activities are interconnected by finish-start precedence relations, and pre-emption is not allowed. Then, the ɛ-constraint optimization method is used to solve 24 different-sized instances, ranging from 5 to 120 activities, and report the makespan, total cost and CPU time. A set of Pareto-optimal solutions are determined for some instances, and sensitivity analyses are performed to find the impact of changing parameters on objective values.

Findings

Results highlight the importance of resource transportability assumption on project completion time and cost, providing useful insights for decision makers and practitioners.

Originality/value

A novel bi-objective optimization model is proposed to deal with the multi-site MRCPSP, considering both the cost and time of resource transportation between multiple sites. To the best of the authors’ knowledge, none of the studies in the project scheduling area has yet addressed this problem.

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来源期刊
CiteScore
5.50
自引率
12.50%
发文量
52
期刊介绍: Journal of Modelling in Management (JM2) provides a forum for academics and researchers with a strong interest in business and management modelling. The journal analyses the conceptual antecedents and theoretical underpinnings leading to research modelling processes which derive useful consequences in terms of management science, business and management implementation and applications. JM2 is focused on the utilization of management data, which is amenable to research modelling processes, and welcomes academic papers that not only encompass the whole research process (from conceptualization to managerial implications) but also make explicit the individual links between ''antecedents and modelling'' (how to tackle certain problems) and ''modelling and consequences'' (how to apply the models and draw appropriate conclusions). The journal is particularly interested in innovative methodological and statistical modelling processes and those models that result in clear and justified managerial decisions. JM2 specifically promotes and supports research writing, that engages in an academically rigorous manner, in areas related to research modelling such as: A priori theorizing conceptual models, Artificial intelligence, machine learning, Association rule mining, clustering, feature selection, Business analytics: Descriptive, Predictive, and Prescriptive Analytics, Causal analytics: structural equation modeling, partial least squares modeling, Computable general equilibrium models, Computer-based models, Data mining, data analytics with big data, Decision support systems and business intelligence, Econometric models, Fuzzy logic modeling, Generalized linear models, Multi-attribute decision-making models, Non-linear models, Optimization, Simulation models, Statistical decision models, Statistical inference making and probabilistic modeling, Text mining, web mining, and visual analytics, Uncertainty-based reasoning models.
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