Optimization of precast production scheduling for rail track slab

Abstract

Design, production and installation of track slabs are critical technologies of high-speed rail which has become an important trend of the transportation development across the world. This paper mainly investigates the scheduling arrangements and optimization of precast production of track slabs. A Flow-Shop Multi-Objective Optimization Scheduling Model (FSMSM) has been developed and solved by a Hybrid Genetic and Ant Colony Algorithm (HGACA). Comparisons among HGACA, single Genetic Algorithm, Ant Colony Algorithm and classical heuristic rules show that the HGACA could obtain better schedules for the model. By means of co-scheduling factory production and engineering construction, scientific and efficient precast production has been promoted and management ability of the industry has been enhanced. It may help manufacturers save enterprise resource, reduce labor consumption, decrease inventory costs, enhance production flexibility and improve enterprise's Level of Service.