A Double Optimum New Solution Method Based on EVA and Knapsack

Theofanis Petropoulos (), Paris Patsis, Konstantinos Liapis and Evangelos Chytis
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Theofanis Petropoulos: Department of Economic & Regional Development, Panteion University, Syngrou Av. 136 176-71, 48100 Athens, Greece
Paris Patsis: Department of Economic & Regional Development, Panteion University, Syngrou Av. 136 176-71, 48100 Athens, Greece
Konstantinos Liapis: Department of Economic & Regional Development, Panteion University, Syngrou Av. 136 176-71, 48100 Athens, Greece
Evangelos Chytis: Department of Accounting and Finance, University of Ioannina, Campus Preveza, 48100 Preveza, Greece

JRFM, 2024, vol. 17, issue 11, 1-22

Abstract: Optimizing resource allocation often requires a trade-off between multiple objectives. Since projects must be fully implemented or not at all, this issue is modeled as an integer programming problem, precisely a knapsack-type problem, where decision variables are binary (1 or 0). Projects may be complementary/supplementary and competitive/conflicting, meaning some are prerequisites for others, while some prevent others from being implemented. In this paper, a two-objective optimization model in the energy sector is developed, and the Non-dominated Sorting Genetic Algorithm III (NSGA III) is adopted to solve it because the NSGA-III method is capable of handling problems with non-linear characteristics as well as having multiple objectives. The objective is to maximize the overall portfolio’s EVA (Economic Value Added). EVA is different from traditional performance measures and is more appropriate because it incorporates the objectives of all stakeholders in a business. Furthermore, because each project generates different kilowatts, maximizing the total production of the portfolio is appropriate. Data from the Greek energy market show optimal solutions on the Pareto efficiency front ranging from (14.7%, 38,000) to (11.91%, 40,750). This paper offers a transparent resource allocation process for similar issues in other sectors.

Keywords: portfolio management; mathematic programming; finance; decision-making; multi-objective optimization; mathematics of quantitative finance; mathematical models in optimal portfolio theory (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2024
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