Space-Time Repetitive Project Scheduling Considering Location and Congestion

Abstract

Repetitive projects account for a large proportion of construction projects. Different from standard project scheduling problems, scheduling such projects requires considering both location and congestion, which is referred to as a space-time project scheduling problem. The literature on this kind of project scheduling is rather limited. In this paper, the authors study this problem and formulate it as a multiobjective mixed-integer programming problem which minimizes resource reallocation and congestion. A nondominated sorting genetic algorithm II (NSGAII) modified by integrating an electromagnetism-like mechanism, NSGAII-EM, is developed to solve this problem. Refurbishing a multistory hotel is used as an example to illustrate and validate the proposed method. Compared with the problem not considering location or congestion, the proposed model can offer better use of resources and can improve productivity through a better and safer working environment on the construction site. Furthermore, NSGAII-EM is validated by comparing it with NSGAII, strength Pareto evolutionary algorithm II (SPEAII), Pareto envelope-based selection algorithm II (PESAII), multiobjective evolutionary algorithm based on decomposition (MOEA/D), multiobjective particle swarm optimization (MOPSO), SPEAII-electromagnetism-like mechanism (SPEAII-EM), PESAII-electromagnetism-like mechanism (PESAII-EM), and MOEA/D-electromagnetism-like mechanism (MOEA/D-EM).