INTEGRATING PATH PLANNING, ROUTING, AND SCHEDULING FOR LOGISTICS OPERATIONS IN MANUFACTURING FACILITIES

Abstract

This article considers the following manufacturing/logistics problem: an autonomous vehicle (AV) is requested to serve a set of pickup and delivery (P/D) stations in the shop floor of a modern factory providing P/D tasks while moving safely (i.e., avoiding any collision with obstacles) in its environment. A two-sided time window associated with each P/D station brackets the service time to within a specified interval. A tour for AV is considered legal if it (a) is collision free, (b) passes through each P/D station exactly once, and (c) satisfies the service time restrictions imposed by the P/D stations. A legal tour always starts and ends at a depot. The problem is thereby dual NP-hard because it combines the characteristics of path planning and those of vehicle routing and scheduling problems. The objective is to determine the shortest possible legal tour for AV. A new method is introduced to solve the problem accomplished in two successive phases: first, AV's environment is mapped into a 2D B-spline surface embedded in 3D Euclidean space using a robust geometric model. Then, the generated surface is searched using a genetic algorithm for an optimum legal tour that satisfies the requirements of the vehicle's mission. The performance of the proposed method is investigated and discussed through characteristic simulated experiments.