Differential evolution and Population-based simulated annealing for truck scheduling problem in multiple door cross-docking systems

Abstract

Scheduling of inbound and outbound trucks, which decides on the succession of truck processing at the receiving and shipping dock, is particularly significant to ensure a rapid turnover and on-time deliveries. In this paper, we adopt Just-In-Time (JIT) philosophy in truck scheduling problem, where the interchangeability of products, ready times for both inbound and outbound trucks and also different transshipment time between receiving and shipping doors are considered. The objective is to minimize total earliness and tardiness for outbound trucks, in such systems. A mixed integer programming model is developed to formulate the problem and is solved optimally in small-sized instances with ILOG CPLEX solver. Also to solve medium to large-sized cases, two meta-heuristics called Differential evolution and Population-based simulated annealing are employed. The meta-heuristics are tuned by the response surface methodology. Finally, the performances of the meta-heuristics are compared with CPLEX solver in small-sizes instances, and also to each other and Pure Random search in medium to large-sized problems. The computational results demonstrates the efficiency of our meta-heuristics.