A Bi-Objective Mathematical Model for the Multi-Skilled Resource-Constrained Project Scheduling Problem Considering Reliability: An AUGMECON2VIKOR Hybrid Method

TL;DR

This paper introduces a new bi-objective mathematical model for the multi-skilled resource-constrained project scheduling problem considering reliability, and proposes a hybrid solution method that improves solution quality and computational efficiency.

Contribution

It develops a novel reliability-aware model for MSRCPSP and introduces the AUGMECON2VIKOR hybrid method to effectively solve complex instances.

Findings

Project makespan reduced by 2.55% on average

Project cost decreased by 2.80% on average

CPU time decreased by 543 seconds compared to baseline

Abstract

In recent years, resources with multiple skills have received attention as an extension of the resource-constrained project scheduling problem known as MSRCPSP. Although the disruption rate is well-estimated in today's manufacturing projects, its impact on project makespan and cost need further investigation. Hence, this study presents a novel mathematical model for the MSRCPSP considering reliability, namely MSRCPSPR. The model proposes both objectives of minimizing project makespan and project cost. The MSRCPSP is an NP-hard problem, and including reliability constraints, as proposed in this paper, makes solving the problem more intractable. To cope with the computational challenges of solving the problem, a combination of an enhanced version of the epsilon-constraint method as well as an augmented version of the VIKOR algorithm, namely AUGMECON2VIKOR, is employed to solve benchmark instances j10 and j20 from the PSPLIB. A comparative analysis demonstrates the performance of the proposed method, and the sensitivity analysis represents the effects of positive reliable constraints on the objective functions. Employing the proposed method, the project makespan and cost are reduced by nearly 2.55% and 2.80% in j10 on average. CPU time is also decreased by about 543 seconds in comparison to the epsilon-constraint method.