Simultaneous Scheduling of Assembly and Production Shops Using GA based Heuristic

This paper addresses a scheduling problem in an industry that manufactures machines. The manufacturing facility of the industry consist of two sections namely production shops and assembly shops. Production encompasses four subsections in it. Production shop is commonly shared by the components of different machines. But the assembly shops have independent section for each machine. Due to the sharing of production shops the components are not delivered in time to the assembly shop which delays the assembly of a product. The above problem is addressed by simultaneously scheduling the production and assembly shops with an objective criterion of minimum penalty cost. The production environment is of job shop in nature. The schedule generated accounts the alternative routing as it increases the flexibility in scheduling. Job shop problem are combinatorial optimization problems, account of alternative routing increase the complexity of the problem. The above problem becomes NP hard in nature. Meta heuristics are evolving as a promising alternative to address the NP hard problems. Genetic algorithm one among the Meta heuristic is used to evolve the simultaneous schedule of production and assembly shops and it is illustrated with the different products models developed to represent the machines of the company.