Bicriteria multiresource generalized assignment problem

Karsu, Özlem; Azizoğlu, Meral

doi:10.1002/nav.21607

Cited by 10 publications

(4 citation statements)

References 29 publications

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“…Taking the workload allocation example, a motivating case is a problem faced by a firm working in the heating ventilation and air conditioning (HVAC) sector in Turkey ( Karsu and Azizog l u, 2012 ;Karsu & Azizog l u, 2014 ). The manager faces the problem of assigning staff (agents) to tasks such that once assigned the agent will perform the task for multiple periods.…”

Section: The Problem Of Fair Allocation and Application Domainsmentioning

confidence: 99%

Capturing preferences for inequality aversion in decision support

Karsu

Morton²,

Argyris

2018

European Journal of Operational Research

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We investigate the situation where there is interest in ranking distributions (of income, of wealth, of health, of service levels) across a population, in which individuals are considered preferentially indistinguishable and where there is some limited information about social pref- erences. We use a natural dominance relation, generalized Lorenz dominance, used in welfare comparisons in economic theory. In some settings there may be additional information about preferences (for example, if there is policy statement that one distribution is preferred to an- other) and any dominance relation should respect such preferences. However, characterising this sort of conditional dominance relation (specifically, dominance with respect to the set of all symmetric increasing quasiconcave functions in line with given preference information) turns out to be computationally challenging. This challenge comes about because, through the as- sumption of symmetry, any one preference statement (“I prefer giving $100 to Jane and $110 to John over giving $150 to Jane and $90 to John”) implies a large number of other preference statements (“I prefer giving $110 to Jane and $100 to John over giving $150 to Jane and $90 to John”; “I prefer giving $100 to Jane and $110 to John over giving $90 to Jane and $150 to John”). We present theoretical results that help deal with these challenges and present tractable linear programming formulations for testing whether dominance holds between any given pair of distributions. We also propose an interactive decision support procedure for ranking a given set of distributions and demonstrate its performance through computational testing

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Section: The Problem Of Fair Allocation and Application Domainsmentioning

confidence: 99%

Capturing preferences for inequality aversion in decision support

Karsu

Morton²,

Argyris

2018

European Journal of Operational Research

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“…It is a modification of best‐first search that creates a search tree, and then uses breadth‐first search. It lends itself easily to providing multiple solutions (by sampling at various stages of the beam search) that are typically diverse in the spending of the portfolios generated, and can be sorted to provide a set of nondominated solutions, which we can later use to seed our genetic algorithm (Karsu & Azizoğlu, 2014). The fact that multiple solutions can be evaluated at every stage of the beam search also makes it attractive due to the opportunity for parallelization it offers when being implemented on a computing system with access to a parallel computing cluster.…”

Section: Modeling Frameworkmentioning

confidence: 99%

A generalized decision support framework for large‐scale project portfolio decisions

et al. 2021

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Project portfolio selection (PPS) is a complex problem faced by major companies whenever there are multiple funding opportunities with insufficient budget to fund them all. In this paper, we present our work on a PPS decision support tool that has become a fundamental part of the project portfolio decision process at Intel Corporation across its largest product and market divisions. The paper builds on a previous publication that outlines the decision support tool's bicriteria optimization model by providing a solution procedure that is capable of solving real-life PPS problems within time frames acceptable to decision makers, as well as providing further details on the data collection and the decision-making process. We also report on various analysis and visualization tools that have been built to allow decision makers to interact with promising solutions provided by the decision support tool. One of the contributions of the paper is to present a typology of the important dependencies between projects that needs to be considered, and provide details on how they are incorporated in the decision support tool's optimization engine. We discuss important implementation details on the decision-making process and the agents involved, and conclude by describing real-life experiences on how the framework can enable intuitive decision-making when choosing portfolios that best satisfy the organization's business goals.

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“…Özçelik ve Saraç [39] uygunluk kısıtları olan darboğaz MRGAP problemi için bir matematiksel model önermişlerdir. Karsu ve Azizoglu [40], toplam yükün enküçüklenmesi ve en çok yüke sahip ajanın yükünün enküçüklenmesi olmak üzere iki amaçlı MRGAP'ı ele almıştır. MRGAP literatürü çözüm yöntemleri açısından incelendiğinde, çözüm yöntemlerinin kesin çözüm yöntemleri ( [30], [36]- [39]), sezgisel ([33]- [35], [40]) ve metasezgisel yöntemler ( [40]) olarak gruplanabileceği görülmektedir.…”

Section: Gi̇ri̇ş (Introduction)unclassified