Single mobile robot scheduling: a mathematical modeling of the problem with real-world implementation

Abstract

In this paper, the authors focus on the mathematical formulation of the single mobile robot scheduling problem concerning an intelligent manufacturing system (IMS) with n parts, m machine tools and one mobile robot used to transport parts between machines. Furthermore, the following five flexibility types of the scheduling plans are analyzed: (i) process, (ii) sequence, (iii) machine tool, (iv) tool and (v) tool access direction (TAD) flexibility. Since there are numerous ways to schedule the manufacturing resources in an IMS, this problem is considered to be NP-hard in terms of combinatorial optimization. In order to solve this type of optimization problem, the authors propose three metaheuristic algorithms: Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA). All the algorithms are implemented in MATLAB software package and tested on real-world problem. The experimental results show that the optimal solution obtained by the WOA is superior to the optimal solutions obtained by two other algorithms.