Using Holistic Multicriteria Assessments: The Convex Cones Approach

2018

Omega

Self Cite

In this study, we develop decision support tools for policy makers that will help them make choices among a set of allocation alternatives. We assume that alternatives are evaluated based on their benefits to different users and that there are multiple benefit (output) types to consider. We assume that the policy maker has both efficiency (maximizing total output) and equity (distributing outputs across different users as fair as possible) concerns. This problem is a multicriteria decision making problem where the alternatives are represented with matrices rather than vectors.We develop interactive algorithms that guide a policy maker to her most preferred solution (a set of most preferred solutions), which are based on utility additive (UTA) and convex cone methods. Our computational experiments demonstrate the satisfactory performance of the algorithms. We believe that such decision support tools may be of great use in practice and help in moving towards fair and efficient allocation decisions. Bu çalışmada, karar vericilere proje alternatifleri arasında başlatılacak olanı seçerken yardımcı olacak karar destek sistemleri geliştirilmiştir. Proje alternatiflerinin birden fazla çıktının birden fazla kullanıcıya farklı dagılımlarına karşılık geldigi bu problemde, karar vericilerin alternatifleri sadece dagıtılan çıktının toplam miktarına göre degil, çıktıların kullanıcılara nasıl dagıtıldıgına göre de degerlendirdigi varsayılmaktadır. Bu problem, alternatiflerin vektörler yerine matrislerle gösterildigi, çok kriterli bir karar verme problemidir. KeywordsKarar vericiyi, en çok tercih ettigi alternatife yönlendirecek iki ayrı interaktif yöntem geliştirilmiştir. Bu yöntemlerden ilki, toplanabilir fayda skorları yöntemine (UTA) dayanırken, digeri konveks koni yöntemi kullanılarak geliştirilmiştir. Elde ettigimiz sonuçlar dogrultusunda iki yöntemin de yeterli performansa sahip oldugu gözlemlenmiştir. Bu tür karar destek sistemlerinin politika yapım süreçlerinde karar vericileri eşitlikçi ve verimli alternatiflere yönlendirmekte faydalı olacagına inanıyoruz.

Section: Use Of Convex Cones In Classical Mcdm Choice Problemsmentioning

confidence: 99%

Section: Use Of Convex Cones In Classical Mcdm Choice Problemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Generalized Lorenz Dominance Is Introduced As An Extension Omentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Equitable decision making approaches over allocations of multiple benefits to multiple entities

Kaynar

2018

Omega

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Trading off health and financial protection benefits with multiobjective optimization

Morton

2020

Health Economics

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Countries which are introducing a system of Universal health coverage have to make a number of key tradeoffs, of which one is the tradeoff between the level of coverage and the degree to which patients are exposed to potentially catastrophic financial risk. In this study, we first present a way in which decision makers might be supported to focus on in a particular part of the tradeoff curve and ultimately choose an efficient solution. We then introduce some multiobjective optimization models for generating the tradeoff curves given data about potential treatment numbers, costs, and benefits. Using a dataset from Malawi, we demonstrate the approach and suggest a core index metric to make specific observations on the individual treatments. Moreover, as there has been some debate about the best way to measure financial exposure, we also investigate the extent to sensitivity of our results to the precise technical choice of financial exposure metric. Specifically, we consider two metrics, which are the total number of cases protected from catastrophic expenditure and a convex penalty function that penalizes out‐of‐pocket expenditures in an increasingly growing way, respectively.

Solution approaches for equitable multiobjective integer programming problems

Bashir

2020

Ann Oper Res

Self Cite

We consider multi-objective optimization problems where the decision maker (DM) has equity concerns. We assume that the preference model of the DM satisfies properties related to inequity-aversion, hence we focus on finding nondominated solutions in line with the properties of inequity-averse preferences, namely the equitably nondominated solutions. We discuss two algorithms for finding good subsets of equitably nondominated solutions. The first approach is an extension of an interactive approach developed for finding the most preferred nondominated solution when the utility function is assumed to be quasiconcave. We find the most preferred equitably nondominated solution when the utility function is assumed to be symmetric quasiconcave. In the second approach we generate an evenly distributed subset of the set of equitably nondominated solutions to be considered further by the DM. We show the computational feasibility of the two algorithms on equitable multi-objective knapsack problem, in which projects in different categories are to be funded subject to a limited budget. We perform experiments to show and discuss the performances of the algorithms.