Abstract

In real-world environments, selecting the right contractor is an important issue which considerably influences completion time, total cost and quality of performing the project. This paper deals with the multi-mode resource constrained project scheduling problem (MRCPSP) and contractor selection (CS) in an integrated manner. In fact, each activity is assigned to a contractor, an execution mode is selected for each activity, and the start/finish times of activities are determined. This paper presents a bi-objective optimization model to deal with MRCPSP-CS, aiming to minimize the total cost and completion time of the project, simultaneously. Then, four multi-objective decision making (MODM) techniques are used to solve the proposed model. Since none of MODM techniques dominates other ones, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to assess the performance of MODM techniques, confirming that MCGP-U outranks other ones. Finally, the augmented $\epsilon$-Constraint method is used to solve some test problems, and perform sensitivity analysis on the number of contractors. Sensitivity analyses show that by increasing the number of available contractors, the Pareto front is significantly improved, and the Number of Pareto-optimal Solutions (NPS) increases. This helps decision maker(s) make appropriate decisions in a more flexible manner.

摘要

在现实环境中，选择合适的承包商是一个重要问题，它会极大地影响完成时间、总成本和执行项目的质量。本文以综合方式处理多模式资源受限项目调度问题（MRCPSP）和承包商选择（CS）。实际上，每个活动都分配给一个承包商，为每个活动选择一种执行模式，并确定活动的开始/结束时间。本文提出了一种双目标优化模型来处理 MRCPSP-CS，旨在同时最小化项目的总成本和完成时间。然后，使用四种多目标决策（MODM）技术来解决所提出的模型。由于没有一种 MODM 技术能支配其他技术，通过与理想解决方案相似的偏好顺序技术 (TOPSIS) 用于评估 MODM 技术的性能，确认 MCGP-U 优于其他技术。最后，增强$\epsilon$-约束方法用于解决一些测试问题，并对承包商数量进行敏感性分析。敏感性分析表明，通过增加可用承包商的数量，帕累托前沿显着改善，帕累托最优解（NPS）的数量增加。这有助于决策者以更灵活的方式做出适当的决策。