Treffer: Solving flexible job shop scheduling problem with worker flexibility and outsourcing service time windows using an adaptive dual-population memetic algorithm.

Within contemporary manufacturing systems, optimising the flexible job shop scheduling problem (FJSP) requires production managers to navigate an important reality often absent. It involves integrating flexible human resources with the strategic use of outsourcing while respecting the supplier's production plan. Under the background, we define the flexible job shop scheduling problem with worker flexibility and outsourcing service time windows (FJSPWO). To address it, a mixed integer linear programming model is developed, and based on this, an effective adaptive dual-population memetic algorithm (ADPMA) is proposed, including three innovations: a heuristic initialisation strategy is designed to increase the proportion of feasible solutions; a dynamic dual-population co-evolution framework based on the golden section is presented, which balances the exploration and exploitation; the unique critical-path of FJSPWO is defined, and a problem-specific neighbourhood structure that satisfies resource coupling relationship and outsourcing constraints is designed, further improving the convergence accuracy. In the experiment, ADPMA achieves the best results on 96.67% of the problems compared to other algorithms, from which we derive actionable managerial insights for production planning. Finally, the proposed method is applied to a practical case in one ship structural component manufacturing enterprise, reducing the makespan by 39.61%. [ABSTRACT FROM AUTHOR]

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