A Comparison between Memetic Algorithm and Genetic Algorithm for an Integrated Logistics Network with Flexible Delivery Path

Abstract The distribution/allocation problem is known as one of the most comprehensive strategic decision. In real-world cases, it impossible to solve a in traditional ways with acceptable time. Hence researchers develop efficient non-traditional techniques for large-term operation whole supply chain. These provide near optimal solutions particularly large-scale test problems. This paper presents an integrated chain model which flexible delivery path. As solution methodology, we apply memetic algorithm neighborhood search mechanism and novelty population presentation method called “extended random path direct encoding method.” To illustrate performance proposed algorithm, LINGO optimization software serves comparison basis small size large-size cases that are dealing real world, classical genetic second metaheuristic considered compare results show efficiency algorithm.