A Novel Maximin-Based Multi-Objective Evolutionary Algorithm Using One-by-One Update Scheme for Multi-Robot Scheduling Optimization

With the continuous development of E-commerce, warehouse logistics is also facing emerging challenges, including more batches orders and shorter order processing cycles. When need to be processed simultaneously, some existing task scheduling methods may not able give a suitable plan, which delays reduces efficiency warehouse. Therefore, intelligent system that uses autonomous robots for automated storage becoming mainstream. Based on this concept, we propose multi-robot cooperative in The aim drive many an perform distributed tasks optimal (e.g., time-saving energy-conserved) way. In paper, model For model, design maximin-based multi-objective algorithm, one-by-one update scheme select individuals. two indicators are devised discriminate equivalent individuals with same maximin fitness value environmental selection process. results benchmark test suite show our algorithm indeed useful optimizer. Then it applied settle problem intelligence Simulation experiment demonstrate proposed real-world problem.