A node sequence-based ant colony optimisation algorithm for die scheduling problem with twin-crane transportation

With the increasing demand for multi-variety and small-batch products, it's necessary to frequently dispatch and replace the progressive press dies on the stamping production lines to ensure the diversity of processed automobile covering parts. This paper formulates a die scheduling problem with twin-crane transportation (DSP-TCT) encountered in the stamping production line, which concentrates on the scheduling of transporting dies between the production line and warehouse by twin cranes with satisfying crane distance constraint, die position constraint, and precedence constraint. To solve DSP-TCT, this paper proposes a node sequence-based ant colony optimisation algorithm (NS-ACO). In this algorithm, each node represents a single die transportation task with action and time information executed by the twin cranes. The combination of adjacent nodes with a high time utilisation rate can be accumulated as heuristic priority knowledge for guiding optimisation. To demonstrate the effectiveness of the NS-ACO algorithm, numerical experiments with three different die stacking strategies are executed.

Automated summary

This paper addresses the die scheduling problem encountered in stamping production lines and proposes an NS-ACO algorithm to optimize die transportation. The algorithm represents individual die transportation tasks as nodes, with combinations of adjacent nodes used as heuristic priority knowledge.