Task-Location Assignment Problem in Planning Horizon
DOI:
https://doi.org/10.7494/dmms.2026.20.1.8153Keywords:
task-location allocation, mathematical programming, Mixed-Integer Linear Programming, heuristics, greedy scheduling algorithm, priority-based scheduling algorithmAbstract
Efficient task allocation in production environments is essential for optimizing resource utilization and minimizing operating costs. This paper proposes a Mixed-Integer Linear Programming (MILP) model for the Task-Location Assignment Problem in Planning Horizon, with the objective of minimizing total operating costs. Additionally, two heuristic algorithms – a greedy scheduling algorithm and a priority-based scheduling algorithm – were developed to generate feasible solutions quickly. Computational experiments were conducted using real-world production process data across various scenarios. The results indicate that the proposed MILP model achieves an average cost reduction of approximately 11% compared to the greedy scheduling algorithm and about 6% compared to the priority-based scheduling algorithm. The results demonstrate the practical value of mathematical optimization in reducing internal production supply costs while supporting the efficient allocation of production tasks to available locations.
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