An order dispatcher for dispersed manufacturers solved by a mixed-variable hybrid genetic algorithm

This paper describes a new solution for an order dispatching problem (ODP) within a distributed manufacturing environment. A mathematical model has been developed to describe the ODP, including both assigning orders to manufacturers and determining the completion times while satisfying a set of constraints. This model has two types of variables: 0-1 decision variables and integer variables that make it a non-linear mixed-variables integer programming model. The usage rate of parts inventory is taken into consideration to avoid parts devaluation. To solve the problem, a novel hybrid genetic algorithm (GA) with a new evolution strategy has been introduced. The hybrid GA can provide more survival chances in the evolving competition for outstanding individuals and introduce potentially excellent individuals to the next generation. To find the appropriate completion times for each order, the hybrid GA embeds a mini-scheduling algorithm to arrange the executing sequence of orders for each manufacturer. The computation results have shown that the proposed hybrid GA can find more satisfactory solutions than the GA with traditional evolution strategies, particularly as the problem size increases with the number of orders.