{"ID":2846924,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.00762","arxiv_id":"2511.00762","title":"Automatic Policy Search using Population-Based Hyper-heuristics for the Integrated Procurement and Perishable Inventory Problem","abstract":"This paper addresses the problem of managing perishable inventory under multiple sources of uncertainty, including stochastic demand, unreliable supplier fulfillment, and probabilistic product shelf life. We develop a discrete-event simulation environment to compare two optimization strategies for this multi-item, multi-supplier problem. The first strategy optimizes uniform classic policies (e.g., Constant Order and Base Stock) by tuning their parameters globally, complemented by a direct search to select the best-fitting suppliers for the integrated problem. The second approach is a hyper-heuristic approach, driven by metaheuristics such as a Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). This framework constructs a composite policy by automating the selection of the heuristic type, its parameters, and the sourcing suppliers on an item-by-item basis. Computational results from twelve distinct instances demonstrate that the hyper-heuristic framework consistently identifies superior policies, with GA and EGA exhibiting the best overall performance. Our primary contribution is verifying that this item-level policy construction yields significant performance gains over simpler global policies, thereby justifying the associated computational cost.","short_abstract":"This paper addresses the problem of managing perishable inventory under multiple sources of uncertainty, including stochastic demand, unreliable supplier fulfillment, and probabilistic product shelf life. We develop a discrete-event simulation environment to compare two optimization strategies for this multi-item, mult...","url_abs":"https://arxiv.org/abs/2511.00762","url_pdf":"https://arxiv.org/pdf/2511.00762v1","authors":"[\"Leonardo Kanashiro Felizardo\",\"Edoardo Fadda\",\"Mariá Cristina Vasconcelos Nascimento\"]","published":"2025-11-02T01:27:52Z","proceeding":"cs.NE","tasks":"[\"cs.NE\",\"math.OC\"]","methods":"[\"Large Language Model\"]","has_code":false}