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    A set partitioning based goal programming model for the team formation problem
    (Wiley, 2022) Das, Gulesin Sena; Altinkaynak, Busra; Gocken, Tolunay; Turker, Ahmet Kursad
    In this paper, we offer a multi-objective set-partitioning formulation for team formation problems using goal programming. Instead of selecting team members to teams, we select suitable teams from a set of teams. This set is generated using a heuristic algorithm that uses the social network of potential team members. We then utilize the proposed multi-objective formulation to select the desired number of teams from this set that meets the skill requirements. Therefore, we ensure that selected teams include individuals with the required skills and effective communication with each other. Two real datasets are used to test the model. The results obtained with the proposed solution are compared with two well-known approaches: weighted and lexicographic goal programming. Results reveal that weighted and lexicographic goal programming approaches generate almost identical solutions for the datasets tested. Our approach, on the other hand, mostly picks teams with lower communication costs. Even in some cases, better solutions are obtained with the proposed approach. Findings show that the developed solution approach is a promising approach to handle team formation problems.
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    Modeling an Industrial Symbiosis Network using Bilevel Programming
    (Institute of Electrical and Electronics Engineers Inc., 2021) Das, Gulesin Sena; Yesilkaya, Murat; Altinkaynak, Busra; Birgoren, Burak
    In this study, we propose a bilevel programming model for a theoretical industrial symbiosis network located in an Eco-Industrial Park. Plants in this forest products-based network comprising a sawmill, a plywood manufacturer, a particleboard producer, a fiberboard producer and a pellet producer aim to minimize their production related costs. On the other hand, the park authority aims to minimize the use of raw materials to foster by-product exchange in the park. Therefore, we propose a bilevel programming model where the park authority is the upper-level decision-maker/leader and the plants in the network are the lower-level decision makers/followers. Our aim is to investigate the effects of industrial symbiosis on emissions and the profitability of the companies. Results s how only by decreasing raw material use, companies in such a network could stay profitable without increasing emissions. © 2021 IEEE.