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    A fuzzy approach for the reviewer assignment problem
    (Pergamon-Elsevier Science Ltd, 2014) Das, G. Sena; Gocken, Tolunay
    Assignment of experts to project proposals is a significant task for funding agencies which have to assess the potential value of the research and development (R&D) projects through peer review. The problem is known as reviewer assignment problem and has real-world applications in funding agencies, conferences and research journals. Given a set of experts and a set of proposals; the problem can be defined as assigning the most suitable experts to the proposals under some constraints, which are generally encountered by funding agencies. In this study, a fuzzy model is offered to solve the reviewer assignment problem. The objective of the model is to maximize the total matching degree of assigned experts under some constraints such as cost of forming a panel and the size of a panel. The matching degrees are defined using linguistic variables to denote the expertise of each expert with respect to each proposal. The fuzzy mathematical model, which also takes into account different constraints related to the problem, is solved via the selected fuzzy ranking methods namely; the signed distance method and the method of ranking fuzzy numbers with integral value. The solution of an example problem - inspired from a real-life situation with both of the mentioned methods revealed the effectiveness of the solution approach. It is believed that the use of the offered fuzzy approach could improve the accuracy of the decisions made by funding agencies. (C) 2014 Elsevier Ltd. All rights reserved.
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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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    Direct Solution of Time-Cost Tradeoff Problem with Fuzzy Decision Variables
    (Taylor & Francis Inc, 2016) Gocken, Tolunay; Baykasoglu, Adil
    Project time-cost tradeoff problem is concerned with shortening project duration time with minimum cost. Due to uncertain environment conditions, such as inflation, climate changes, space congestion, productivity level, lack of accurate data, etc., there can be uncertainty in the parameters. The uncertainty in the parameters can be modeled using fuzzy set theory. In this study, a fuzzy time-cost tradeoff problem with fuzzy normal and crash durations, and fuzzy duration of activities and occurrence time of events is handled. The fuzzy time-cost tradeoff problem is solved directly by making use of a fuzzy ranking method and the tabu search (TS) algorithm.
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    Improvement of a Genetic Algorithm Approach for the Solution of Vehicle Routing Problem with Time Windows
    (IEEE, 2017) Gocken, Tolunay; Yaktubay, Meltem; Kılıç, Fatih
    In this study, Vehicle Routing Problem with Time Windows (VRPTW) with known customer demands, a single depot and identical vehicles, is considered. Minimizing the total distance and the total waiting time of the vehicles are determined as objective functions for VRPTW which is capable to serve the customers in a prespecified time interval. A hybridized version of genetic algorithm which is a metaheuristic solution technique with constructive heuristic methods is proposed to produce effective solutions for VRPTW. By using sweep algorithm in initial population generation phase of genetic algorithm, it is planned to begin the search with high quality solution sets and in this way, get more feasible solutions faster. A benchmark problem in the literature is solved and obtained results are compared with the results of genetic algorithm with the nearest neighbor algorithm based algorithm. It is observed that the proposed genetic algorithm beginning with sweep based initial population generation algorithm reaches more effective solutions.