Vehicle scheduling in 2D shop floor environments

Purpose – The purpose of this paper is to develop an efficient method for solving a vehicle scheduling problem (VSP) in 2D industrial environments. An autonomous vehicle is requested to serve a set of work centers in the shop floor providing transport and delivery tasks while avoiding collisions with obstacles during its travel. The objective is to find a minimum in length, collision‐free vehicle routing schedule that serves timely as many as possible work centers in the shop floor. Design/methodology/approach – First, the vehicle's environment is mapped into a 2D B‐Spline surface embedded in 3D Euclidean space using a robust geometric model. Then, a modified genetic algorithm is applied on the generated surface to search for an optimum legal route schedule that satisfies the requirements of the vehicle's mission. Findings – Simulation experiments show that the method is robust enough and can determine in a reasonable computation time a solution to VSP under consideration. Originality/value – There is a gap in the literature for methods that face VSP in shop‐floor environments. This paper contributes to filling this gap by implementing a practical method that can be easily programmed and included in a modern service delivery system.