Bi-objective load balancing multiple allocation hub location: a compromise programming approach
| Autor: | Anass Nagih, Dylan Jones, Shahin Gelareh, Rahimeh Neamatian Monemi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Physics::Physics and Society
Mathematical optimization Computer science traffic engineering load balancing 0211 other engineering and technologies General Decision Sciences 02 engineering and technology Management Science and Operations Research 0502 economics and business Bi objective hub-and-spoke network design Decision Sciences(all) 050210 logistics & transportation 021103 operations research business.industry Quantitative Biology::Molecular Networks 05 social sciences Computer Science::Social and Information Networks Load balancing (computing) Conic section Traffic engineering matheuristic Theory of computation business Compromise programming |
| Zdroj: | Monemi, R N, Gelareh, S, Nagih, A & Jones, D 2020, ' Bi-objective load balancing multiple allocation hub location: a compromise programming approach ', Annals of Operations Research . https://doi.org/10.1007/s10479-019-03421-w |
| DOI: | 10.1007/s10479-019-03421-w |
| Popis: | In this paper we address unbalanced spatial distribution of hub-level flows in an optimal hub-and-spoke network structure of median-type models. Our study is based on a rather general variant of the multiple allocation hub location problems with fixed setup costs for hub nodes and hub edges in both capacitated and uncapacitated variants wherein the number of hub nodes traversed along origin-destination pairs is not constrained to one or two as in the classical models.. From the perspective of an infrastructure owner, we want to make sure that there exists a choice of design for the hub-level sub-network (hubs and hub edges) that considers both objectives of minimizing cost of transportation and balancing spatial distribution of flow across the hub-level network. We propose a bi-objective (transportation cost and hub-level flow variance) mixed integer non-linear programming formulation and handle the bi-objective model via a compromise programming framework. We exploit the structure of the problem and propose a second-order conic reformulation of the model along with a very efficient matheuristics algorithm for larger size instances. |
| Databáze: | OpenAIRE |
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