Finding efficient solutions of the multicriteria assignment problem

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F22%3A10250018" target="_blank" >RIV/61989100:27510/22:10250018 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/B9780128237991000085#" target="_blank" >https://www.sciencedirect.com/science/article/pii/B9780128237991000085#</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/B978-0-12-823799-1.00008-5" target="_blank" >10.1016/B978-0-12-823799-1.00008-5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Finding efficient solutions of the multicriteria assignment problem

Popis výsledku v původním jazyce

The assignment problem (AP) is one of the well-known and most studied combinatorial optimization problems. The single objective AP is an integer programming problem that can be solved with efficient algorithms such as the Hungarian or the successive shortest paths methods. On the other hand, finding and classifying all efficient assignments for a Multicriteria AP (MCAP) remains a controversial issue in Multicriteria Decision Making (MCDM) problems. In this chapter, we tackle the issue by using data envelopment analysis (DEA) models. Importantly, we focus on identifying the efficiency status of assignments using a two-phase algorithm. In phase I, a mixed-integer linear programming (MILP) based on the Free disposable Hull (FDH) model is used to determine minimal complete set (MCS) of efficient assignments. In Phase II, the DEA-BCC model is used to classify efficient assignments as supported or nonsupported. A numerical example is provided to illustrate the presented approach. (C) 2022 Elsevier Inc. All rights reserved.

Název v anglickém jazyce

Finding efficient solutions of the multicriteria assignment problem

Popis výsledku anglicky

The assignment problem (AP) is one of the well-known and most studied combinatorial optimization problems. The single objective AP is an integer programming problem that can be solved with efficient algorithms such as the Hungarian or the successive shortest paths methods. On the other hand, finding and classifying all efficient assignments for a Multicriteria AP (MCAP) remains a controversial issue in Multicriteria Decision Making (MCDM) problems. In this chapter, we tackle the issue by using data envelopment analysis (DEA) models. Importantly, we focus on identifying the efficiency status of assignments using a two-phase algorithm. In phase I, a mixed-integer linear programming (MILP) based on the Free disposable Hull (FDH) model is used to determine minimal complete set (MCS) of efficient assignments. In Phase II, the DEA-BCC model is used to classify efficient assignments as supported or nonsupported. A numerical example is provided to illustrate the presented approach. (C) 2022 Elsevier Inc. All rights reserved.

Druh

C - Kapitola v odborné knize

CEP obor

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OECD FORD obor

10102 - Applied mathematics

Projekt

<a href="/cs/project/GA19-13946S" target="_blank" >GA19-13946S: Hodnocení výkonnosti při výskytu neklasifikovaných faktorů</a><br>

Návaznosti

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

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Multi-Objective Combinatorial Optimization Problems and Solution Methods

ISBN

978-0-12-823799-1

Počet stran výsledku

19

Strana od-do

193-211

Počet stran knihy

290

Název nakladatele

Academic Press

Místo vydání

San Diego

Kód UT WoS kapitoly

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