An Improved Glowworm Swarm Optimization for Vehicle Scheduling in the Iron and Steel Plant Logistics

摘要

The vehicle scheduling in the logistics system of the iron and steel plant is a key issue to the resource allocation and inventory running efficiency of downstream production line. The traditional vehicle scheduling strategy does not analyze the logistics cost and efficiency of inventory scheduling from the aspects of vehicle storage order and time, resulting in low scheduling efficiency and high cost. Taking the right order and time of arrival of the vehicle into the plant and considering the multi-vehicle scheduling can effectively improve the efficiency of inventory and decrease the cost. So, the paper established an integral programming model that can minimize the factory time and the minimum operating cost of the conveyor belt. Then an improved Glowworm Swarm Optimization algorithm was proposed to solve the complex model, and the adaptive strategy was improved to enhance the individual search ability, and the Levy variation was introduced in the process of the Firefly moving. At last, the improved algorithm was validated by the simulation results.