Multi-mobile robots and multi-trips feeding scheduling problem in smart manufacturing system: An improved hybrid genetic algorithm

Abstract

Modern manufacturing systems require timely and efficient production tasks. Any mistakes can have serious consequences which effect the production process obviously. The supply of goods is the beginning of the production process, ensuring that production can proceed normally. Using mobile robots for transportation and supply of production lines can achieve automatic manufacturing. We studied the use of multiple mobile robots to supply multiple production lines. Robots need to return to warehouse when no goods exist. This problem is called a multi-mobile robots and multi-trips feeding scheduling problem. We constructed a mathematical model describing multi-mobile robots and multi-trips feeding scheduling problem, and the objective function is to minimize the transportation cost and waiting cost. To solve this problem, we proposed an improved hybrid genetic algorithm, where a strategy of mixing improved genetic algorithm and tabu search algorithm is adopted to find robots with reasonable routes. Combining genetic algorithm with tabu search algorithm can improve the route planning effect and find a lower cost solution. In the experimental part, it is verified that the proposed algorithm could effectively find reasonable ways for robots to provide services. We also put forward suggestions for the scenarios of using robots in actual production.