Multi-mode resource constrained project scheduling problem along with contractor selection. Issue 2 (3rd May 2021)

• Record Type: Journal Article
• Authors: Nemati-Lafmejani, Reza; Davari-Ardakani, Hamed
• Is Part Of: Infor. Volume 59:Issue 2(2021)
• Page Start: 212
• Page End: 231
• Publication Date: 2021-05-03
• Subjects: Resource constrained project scheduling problem -- multiple modes -- contractor selection -- multi-objective decision making -- augmented ε-constraint method; Operations research -- Periodicals; Electronic data processing -- Periodicals; Systems engineering -- Periodicals; Systems engineering; Electronic data processing; Periodicals; 003.05
• DOI: 10.1080/03155986.2020.1803720
• Languages: English
• ISSNs: 0315-5986

Abstract

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 ε -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.