Profit maximization in congested hub location problems: Demand models and service level constraints

This study investigates a congested hub location problem with the aim of optimizing a service provider’s profit by determining hub locations, capacities, and prices for serving commodities. The study incorporates a price-dependent demand function with a general functional form and models hub operati...

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Vydané v:Transportation research. Part E, Logistics and transportation review Ročník 195; s. 103995
Hlavní autori: Jalili Marand, Ata, Hoseinpour, Pooya
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.03.2025
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ISSN:1366-5545
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Abstract This study investigates a congested hub location problem with the aim of optimizing a service provider’s profit by determining hub locations, capacities, and prices for serving commodities. The study incorporates a price-dependent demand function with a general functional form and models hub operations as M/G/1 queueing systems to address congestion effects. The problem is initially formulated as a mixed-integer nonlinear program, which is subsequently transformed into a mixed-integer second-order cone program, demonstrating solvability with standard off-the-shelf solvers. Through numerical analysis, the study evaluates the influence of different demand functional forms and service time constraints on the optimal network configuration and the service provider’s profitability. •A convex formulation is developed for the congested hub location problem with price-elastic demand.•The model is extended to accommodate uniform and commodity-specific service level constraints.•A commercial solver is employed to solve the proposed model.•Extensive numerical experiments provide valuable managerial insights.
AbstractList This study investigates a congested hub location problem with the aim of optimizing a service provider’s profit by determining hub locations, capacities, and prices for serving commodities. The study incorporates a price-dependent demand function with a general functional form and models hub operations as M/G/1 queueing systems to address congestion effects. The problem is initially formulated as a mixed-integer nonlinear program, which is subsequently transformed into a mixed-integer second-order cone program, demonstrating solvability with standard off-the-shelf solvers. Through numerical analysis, the study evaluates the influence of different demand functional forms and service time constraints on the optimal network configuration and the service provider’s profitability. •A convex formulation is developed for the congested hub location problem with price-elastic demand.•The model is extended to accommodate uniform and commodity-specific service level constraints.•A commercial solver is employed to solve the proposed model.•Extensive numerical experiments provide valuable managerial insights.
ArticleNumber 103995
Author Jalili Marand, Ata
Hoseinpour, Pooya
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Keywords Hub location problem
Congestion
Queuing
Mixed integer second-order cone programming
Pricing
Language English
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Snippet This study investigates a congested hub location problem with the aim of optimizing a service provider’s profit by determining hub locations, capacities, and...
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StartPage 103995
SubjectTerms Congestion
Hub location problem
Mixed integer second-order cone programming
Pricing
Queuing
Title Profit maximization in congested hub location problems: Demand models and service level constraints
URI https://dx.doi.org/10.1016/j.tre.2025.103995
Volume 195
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