Multi-heuristic approach to resource leveling in construction: A hybrid model

Jaeho Son, Purdue University

Abstract

The fluctuation of required resources causes problems in construction scheduling. Thus, researchers developed resource leveling techniques to minimize the deviation between the resource requirements and the desired resource profile. However, the resource leveling problem cannot be solved with exact optimization methods except for small size scheduling problems because it is defined as a discrete combinatorial problem. Thus, researchers used heuristic approaches to get an acceptable solution that may not necessarily be optimal. A multi-heuristic model called local optimizer and two hybrid models combining the local optimizer with Genetic Algorithms and Simulated Annealing is developed for the solution of resource leveling problems. The computational results indicate that these heuristic models produce reasonably good solutions and they are also viable approaches for complex scheduling network.

Degree

Ph.D.

Advisors

Skibniewski, Purdue University.

Subject Area

Civil engineering

COinS