Abstract: To improve the integrated decision-making level of manufacturers for job outsourcing, production and distribution, an integrated outsourcing-production-distribution scheduling problem (IOPDSP) for a single batch processing machine is considered. A 0-1 programming model is established to minimize the total operating cost based on the budget constraint of total outsourcing cost and non-identical job sizes. An improved genetic algorithm (IGA) is designed for solving this problem. A real-world IOPDSP instance in a ceramic company is applied to compare the solution performance of IGA and CPLEX software. It is found that the solution quality of the designed IGA is not worse than that of CPLEX within the limited time of one hour. Through IGA, a sensitivity analysis is made by computer simulations on the tolerance rate of total outsourcing cost, unit time-of-use electricity prices and delivery vehicle types in the above instance. Results show that ceramic companies should ensure that the tolerance rate of total outsourcing cost is not less than 0.75 when arranging firing during peak electricity consumption periods; when the ceramic company is on a highly tight budget for total outsourcing cost, the total operating cost can be reduced by 29.17% and 12.15% via planning the firing of ceramic bodies during off-peak periods of electricity consumption and appropriate selection of vehicle types, respectively.

Key words: joint scheduling, outsourcing, batch processing machine, batch delivery, genetic algorithm