Optimal robust inventory management with volume flexibility: matching capacity and demand with the lookahead peak-shaving policy

Detalhes bibliográficos
Autor(a) principal: Gijsbrechts, Joren
Data de Publicação: 2023
Outros Autores: Imdahl, Christina, Boute, Robert N., Van Mieghem, Jan A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.14/42897
Resumo: We study inventory control with volume flexibility: A firm can replenish using period-dependent base capacity at regular sourcing costs and access additional supply at a premium. The optimal replenishment policy is characterized by two period-dependent base-stock levels but determining their values is not trivial, especially for nonstationary and correlated demand. We propose the Lookahead Peak-Shaving policy that anticipates and peak shaves orders from future peak-demand periods to the current period, thereby matching capacity and demand. Peak shaving anticipates future order peaks and partially shifts them forward. This contrasts with conventional smoothing, which recovers the inventory deficit resulting from demand peaks by increasing later orders. Our contribution is threefold. First, we use a novel iterative approach to prove the robust optimality of the Lookahead Peak-Shaving policy. Second, we provide explicit expressions of the period-dependent base-stock levels and analyze the amount of peak shaving. Finally, we demonstrate how our policy outperforms other heuristics in stochastic systems. Most cost savings occur when demand is nonstationary and negatively correlated, and base capacities fluctuate around the mean demand. Our insights apply to several practical settings, including production systems with overtime, sourcing from multiple capacitated suppliers, or transportation planning with a spot market. Applying our model to data from a manufacturer reduces inventory and sourcing costs by 6.7%, compared to the manufacturer's policy without peak shaving.
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spelling Optimal robust inventory management with volume flexibility: matching capacity and demand with the lookahead peak-shaving policyFlexibilityInventoryPeak-shavingRobust optimizationWe study inventory control with volume flexibility: A firm can replenish using period-dependent base capacity at regular sourcing costs and access additional supply at a premium. The optimal replenishment policy is characterized by two period-dependent base-stock levels but determining their values is not trivial, especially for nonstationary and correlated demand. We propose the Lookahead Peak-Shaving policy that anticipates and peak shaves orders from future peak-demand periods to the current period, thereby matching capacity and demand. Peak shaving anticipates future order peaks and partially shifts them forward. This contrasts with conventional smoothing, which recovers the inventory deficit resulting from demand peaks by increasing later orders. Our contribution is threefold. First, we use a novel iterative approach to prove the robust optimality of the Lookahead Peak-Shaving policy. Second, we provide explicit expressions of the period-dependent base-stock levels and analyze the amount of peak shaving. Finally, we demonstrate how our policy outperforms other heuristics in stochastic systems. Most cost savings occur when demand is nonstationary and negatively correlated, and base capacities fluctuate around the mean demand. Our insights apply to several practical settings, including production systems with overtime, sourcing from multiple capacitated suppliers, or transportation planning with a spot market. Applying our model to data from a manufacturer reduces inventory and sourcing costs by 6.7%, compared to the manufacturer's policy without peak shaving.Veritati - Repositório Institucional da Universidade Católica PortuguesaGijsbrechts, JorenImdahl, ChristinaBoute, Robert N.Van Mieghem, Jan A.2023-10-25T08:41:10Z20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.14/42897eng1059-147810.1111/poms.1406985173446589001075119800001info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-10-31T01:33:51Zoai:repositorio.ucp.pt:10400.14/42897Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:26:08.153491Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Optimal robust inventory management with volume flexibility: matching capacity and demand with the lookahead peak-shaving policy
title Optimal robust inventory management with volume flexibility: matching capacity and demand with the lookahead peak-shaving policy
spellingShingle Optimal robust inventory management with volume flexibility: matching capacity and demand with the lookahead peak-shaving policy
Gijsbrechts, Joren
Flexibility
Inventory
Peak-shaving
Robust optimization
title_short Optimal robust inventory management with volume flexibility: matching capacity and demand with the lookahead peak-shaving policy
title_full Optimal robust inventory management with volume flexibility: matching capacity and demand with the lookahead peak-shaving policy
title_fullStr Optimal robust inventory management with volume flexibility: matching capacity and demand with the lookahead peak-shaving policy
title_full_unstemmed Optimal robust inventory management with volume flexibility: matching capacity and demand with the lookahead peak-shaving policy
title_sort Optimal robust inventory management with volume flexibility: matching capacity and demand with the lookahead peak-shaving policy
author Gijsbrechts, Joren
author_facet Gijsbrechts, Joren
Imdahl, Christina
Boute, Robert N.
Van Mieghem, Jan A.
author_role author
author2 Imdahl, Christina
Boute, Robert N.
Van Mieghem, Jan A.
author2_role author
author
author
dc.contributor.none.fl_str_mv Veritati - Repositório Institucional da Universidade Católica Portuguesa
dc.contributor.author.fl_str_mv Gijsbrechts, Joren
Imdahl, Christina
Boute, Robert N.
Van Mieghem, Jan A.
dc.subject.por.fl_str_mv Flexibility
Inventory
Peak-shaving
Robust optimization
topic Flexibility
Inventory
Peak-shaving
Robust optimization
description We study inventory control with volume flexibility: A firm can replenish using period-dependent base capacity at regular sourcing costs and access additional supply at a premium. The optimal replenishment policy is characterized by two period-dependent base-stock levels but determining their values is not trivial, especially for nonstationary and correlated demand. We propose the Lookahead Peak-Shaving policy that anticipates and peak shaves orders from future peak-demand periods to the current period, thereby matching capacity and demand. Peak shaving anticipates future order peaks and partially shifts them forward. This contrasts with conventional smoothing, which recovers the inventory deficit resulting from demand peaks by increasing later orders. Our contribution is threefold. First, we use a novel iterative approach to prove the robust optimality of the Lookahead Peak-Shaving policy. Second, we provide explicit expressions of the period-dependent base-stock levels and analyze the amount of peak shaving. Finally, we demonstrate how our policy outperforms other heuristics in stochastic systems. Most cost savings occur when demand is nonstationary and negatively correlated, and base capacities fluctuate around the mean demand. Our insights apply to several practical settings, including production systems with overtime, sourcing from multiple capacitated suppliers, or transportation planning with a spot market. Applying our model to data from a manufacturer reduces inventory and sourcing costs by 6.7%, compared to the manufacturer's policy without peak shaving.
publishDate 2023
dc.date.none.fl_str_mv 2023-10-25T08:41:10Z
2023
2023-01-01T00:00:00Z
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dc.language.iso.fl_str_mv eng
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10.1111/poms.14069
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