Using particle swarm optimization techniques for solving multi-mode resource-constrained project scheduling problem

• Main Author: Chandrasekaran, Hari Haran.
• Other Authors: Low Yoke Hean, Malcolm
• Format: Final Year Project
• Language: English
• Published: 2011
• Subjects: DRNTU::Engineering::Computer science and engineering
• Online Access: http://hdl.handle.net/10356/44839
• Institution: Nanyang Technological University

Resource-Constrained Project Scheduling Problems (RCPSP) is one of the most intractable optimization problems in operations research. It can be described as follows: a single project consisting of N activities. Each activity has two kinds of constraints. First, precedence constraints require that an activity cannot start before its immediate predecessor activities have finished. Second, performing each activity requires renewable/non-renewable resources which are limited capacity. This problem is extended to multi-mode resource constrained project scheduling problems (MMRCPSP), which is more related to real world problems, where each activity is executed in one of several modes. Each mode represents the combination of different resources and duration. MRCPSP is an NP-Hard problem and has received increasing attention for the past few years.In this research project, we focus on studying hybrid metaheuristic methods of Particle Swarm Optimization (PSO) for solving Multi-Mode Resource- Constrained Project Scheduling Problems (MMRCPSP). The purpose of this project is to explore and build a hybrid PSO framework that aims to solve MRCPSP efficiently in both quality of schedules and computational time. The obtained results will be applied to project scheduling related industry such as Maritime Rig Building, Construction Work, aircraft maintenance, repair and overhaul project scheduling in aerospace industry.