Imperialist Competitive Algorithm for Subcontractor Selection in Multiple Project Environments

Abstract

Abstract In the current study, Imperialist Competitive Algorithm (ICA) is presented to solve subcontractor selection problem (SSP) in multiple project environments with minimization of general contractor's cost as the objective subject to resource and precedence constraints under two different circumstances. In the first circumstance, the project deadline can be postponed by paying a penalty. While, in the second one, the deadline cannot be postponed. The Random Key (RK) and the subcontractor list representation schemes are employed as encoding procedures and the serial schedule generation scheme (SSGS) is utilized as decoding scheme. Comparing the results of the presented ICA with an exact method and also a Genetic algorithm (GA) utilizing a real case study validates the effectiveness of the proposed algorithm to solve SSP in multiple project environments. The outcomes demonstrate that the proposed ICA is more efficient in the presence of a strict deadline.