New Approaches in Metaheuristics to Solve the Truck Scheduling Problem in a Cross-docking Center

Abstract

Nowadays, cross-docking is one of the main concepts in supply chain management in which products received to a distribution center by inbound trucks which are directly to lead into outbound trucks with a minimum handling and storage costs as the main cost of a cross-docking system. According to the literature, several metaheuristics and heuristics are attempted to solve this optimization model. In this regard, this study utilizes three recent nature-inspired metaheuristics among the first studies in this area. Red Deer Algorithm (RDA), Virus Colony Search (VCS) and Water Wave Optimization (WWO) are three novel nature-inspired algorithms proposed recently to employ their applications in engineering problems. The used algorithm's parameters were selected by Taguchi method to enhance the efficiency of algorithms. The outputs of the proposed algorithms are assessed with each other in different criteria along with statistical analyses and the results yielded by prior works. The results demonstrate that RDA showed a competitive performance compared with mixed other existing algorithms.