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AuthorMejri, Imen
AuthorLayeb, Safa Bhar
AuthorHaouari, Mohamed
AuthorMansour, Farah Zeghal
Available date2023-01-23T08:18:13Z
Publication Date2020
Publication NameEngineering Optimization
ResourceScopus
URIhttp://dx.doi.org/10.1080/0305215X.2019.1603299
URIhttp://hdl.handle.net/10576/38702
AbstractThis article addresses a variant of the Discrete Cost Multicommodity Flow (DCMF) problem with random demands, where a penalty is incurred for each unrouted demand. The problem requires finding a network topology that minimizes the sum of the fixed installation facility costs and the expected penalties of unmet multicommodity demands. A two-stage stochastic programming with recourse model is proposed. A simulation-optimization approach is developed to solve this challenging problem approximately. To be precise, the first-stage problem requires solving a specific multi-facility network design problem using an exact enhanced cut-generation procedure coupled with a column generation algorithm. The second-stage problem aims at computing the expected penalty using a Monte Carlo simulation procedure together with a hedging strategy. To assess the empirical performance of the proposed approach, a Sample Average Approximation (SAA) procedure is developed to derive valid lower bounds. Results of extensive computational experiments attest to the efficacy of the proposed approach.
Languageen
PublisherTaylor and Francis Ltd.
SubjectMonte Carlo simulation
Networks
sample average approximation
simulation-optimization approach
stochastic programming
TitleA simulation-optimization approach for the stochastic discrete cost multicommodity flow problem
TypeArticle
Pagination507-526
Issue Number3
Volume Number52
dc.accessType Abstract Only


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