Operations Research 2025
Abstract Submission

65. Evaluation and Selection of Projects Using TOPSIS-MTPMMCBC with Mixed Multi Cost/Benefit Criteria and Integer Programming

Invited abstract in session WC-5: Multiobjective Decision Making and Integer Programming, stream Decision Theory and Multi-criteria Decision Making.

Wednesday, 13:30-15:00
Room: H7

Authors (first author is the speaker)

1. Semih Eren Karakilic
Darmstadt University of Applied Sciences
2. Yasemin Arici
Darmstadt University of Applied Sciences

Abstract

Companies are typically engaged in planning and executing projects. Due
to developments such as the digitalization of business processes or diversification, there has been an observable increase in the number of projects to be evaluated. Since company resources are limited, their allocation must be carefully planned. Consequently, projects need to be evaluated based on realistic and transparent criteria in order to create an optimal project portfolio. We propose a robust and easily calibrated multi-criteria project evaluation model that encompasses evaluation factors such as the financial criterion measured by Net Present Value (NPV), Risk, Classification, Priority, Strategy, and Sustainability. The model utilizes the Technique for Order of Preference by Similarity to Ideal Solution with multi type projects multi mixed cost and benefit criteria (TOPSIS-MTPMMCBC). A feature of this approach is that the criteria values of the projects can have both negative and positive values. In the next step, the evaluated projects are utilized with Integer Programming (IP), considering constraints such as limited resources, to determine an optimal project portfolio. The model differentiates between optional and mandatory projects. In particular, the criterion of sustainability is gaining importance and becoming a key factor for businesses driven by political and social mandates. In the future, considering sustainability in decision making will become increasingly important and is therefore already integrated into this model. The proposed research may employ Key Performance Indicators (KPIs) as diverse criteria for decision-making. The criteria weights for the sample dataset were objectively calculated using the CRITIC method, and subsequently, a sensitivity analysis was performed.

Keywords

Status: accepted

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