{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:49:14Z","timestamp":1760233754699,"version":"build-2065373602"},"reference-count":28,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,2,17]],"date-time":"2021-02-17T00:00:00Z","timestamp":1613520000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006261","name":"Taif University","doi-asserted-by":"publisher","award":["TURSP-2020\/229"],"award-info":[{"award-number":["TURSP-2020\/229"]}],"id":[{"id":"10.13039\/501100006261","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Inventory-pooling (IP) is an effective tool to mitigate demand uncertainty and variability, to reduce operational costs, and consequently to increase the profit. The major assumptions of the previous works in literature on IP include the following: (1) Independents demand, which satisfy the typical normal independent and identically distributed (iid) random variables; (2) dependents (correlated) symmetric demands, which follows to a multivariate normal distribution. The effect of the dependent asymmetric demand is not yet studied. The aim of this paper is to consider this more realistic case. Indeed, the contribution of this paper is twofold. Firstly, it analyzes both the sensitivity of dependence structure and the levels of skewness of distributions on IP policies in terms of optimal total cost and demand satisfaction constraint. Secondly, both symmetric and asymmetric demand distributions are modeled using various beta distribution and the dependance between demands are modeled using various copulas. A newsvendor problem inspired by the literature, with two decentralized locations and two centralized locations, is considered the empirical study. For each dependance situation, three IP models are considered: inventory centralization, regular transshipments, and independent systems. The results suggest divergences in the decisions in about 9% of cases. Bad choice of marginal distributions given that the copula is appropriate can lead to divergences that vary between 2.2% and 4%, depending on whether the demand distributions are symmetric or asymmetric.<\/jats:p>","DOI":"10.3390\/sym13020328","type":"journal-article","created":{"date-parts":[[2021,2,17]],"date-time":"2021-02-17T04:49:01Z","timestamp":1613537341000},"page":"328","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Sensitivity Analysis of the Optimal Inventory-Pooling Strategies According to Multivariate Demand Dependence"],"prefix":"10.3390","volume":"13","author":[{"given":"Mouna","family":"Derbel","sequence":"first","affiliation":[{"name":"Faculty of Economics and Management of Sfax, University of Sfax, Airport Road Km 4, Sfax 3018, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6561-9141","authenticated-orcid":false,"given":"Wafik","family":"Hachicha","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3793-4814","authenticated-orcid":false,"given":"Awad M.","family":"Aljuaid","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Perez, H.D., Hubbs, C.D., Li, C., and Grossmann, I.E. (2021). Algorithmic Approaches to Inventory Management Optimization. Processes, 9.","DOI":"10.3390\/pr9010102"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Cho, H.C., Hsieh, Y.J., and Huang, L.Y. (2018). Capturing the Risk-Pooling Effect through Inventory Planning and Demand Switching. 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