Lagrangian Dual Decomposition for Two-Echelon Reliable Facility Location Problems with Facility Disruptions

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F20%3A00346174" target="_blank" >RIV/68407700:21730/20:00346174 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1007/978-3-030-61947-3_25" target="_blank" >https://doi.org/10.1007/978-3-030-61947-3_25</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-61947-3_25" target="_blank" >10.1007/978-3-030-61947-3_25</a>

Result language

angličtina

Original language name

Lagrangian Dual Decomposition for Two-Echelon Reliable Facility Location Problems with Facility Disruptions

Original language description

This chapter considers the two-echelon supply chain network design with unreliable facilities when nodes related to facilities in both echelons fail under disruptions. A new mixed-integer programming (MIP) model is proposed for a reliable facility location with possible customer reassignment in different probabilistic scenarios. The maintaining of the materials flow between different echelons of the network is investigated under network disruptions. The performance of global optimization is investigated by comparing this approach with independent and non-integrated optimization. The objective function of the problem seeks to minimize expected costs, including fixed and service costs in the supply chain, such that maintaining the demand flow in both echelons of the network interconnects them. The medium- and large-sized problems are solved using a custom-designed Lagrangian dual decomposition algorithm. Our computational results show that the proposed algorithm is efficient for the given problems, efficiently overcomes the computational complexity of the problems, and provides good-quality solutions within an acceptable time.

Czech name

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Czech description

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Type

C - Chapter in a specialist book

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/LL1902" target="_blank" >LL1902: Powering SMT Solvers by Machine Learning</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Book/collection name

Smart and Sustainable Supply Chain and Logistics – Trends, Challenges, Methods and Best Practices

ISBN

978-3-030-61946-6

Number of pages of the result

17

Pages from-to

363-379

Number of pages of the book

439

Publisher name

Springer

Place of publication

Cham

UT code for WoS chapter

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