Scopus İndeksli Açık & Kapalı Erişimli Yayınlar

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Author: search.filters.author.Kececi, Barissearch.filters.applied.f.rights: search.filters.rights.info:eu-repo/semantics/closedAccess

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    Opposition-Based Variable Neighborhood Descent Algorithm for the Traveling Salesperson Problem with Hotel Selection
    (2022) Akpinar, Ipek Damla; Kececi, Baris
    In this study, The Traveling Salesperson Problem with Hotel Selection (TSPHS) is considered. TSPHS includes daily working time/distance restrictions. This constraint does not allow visiting all points at once. For this reason, the traveler stops (roosts) at a suitable waiting point (hotel) at the end of the day and continues the next day's trip from the point (hotel) where he stayed. There is no obligation to visit each hotel, and a hotel can be visited more than once. A set of ordered nodes starting and ending at a hotel is called a trip, and a set of ordered trips covering all nodes is called a tour. The primary objective of the problem is to minimize the number of trips. The secondary objective is to minimize the total distance of the tour, provided that the time/distance per trip does not exceed the daily working time limit. Since this problem belongs to the NP-hard problem class, the use of the heuristic method has an advantage in terms of the solution time. In our solution approach, the initial solution is obtained using The Nearest Neighbor Algorithm (NN). To improve this solution, the Opposition-Based Variable Neighborhood Descent (OBVND) is used. The performance of the algorithm is evaluated on the test problems in the literature using various criteria. The results are compared with the best solutions available in the literature. The overall results show us that the proposed OBVND approach can find better quality solutions in 2 out of 16 problems in the Set 1 data; in 24 out of 52 problems in the Set 2 data; and in 9 out of 38 problems in Set 3 data.
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    A mixed integer programming formulation for Smashed Sums puzzle: Generating and solving problem instances
    (2021) Kececi, Baris
    Playing mind games and puzzles has 2500 years of known history. Puzzles and games constitute a research domain that is attracting the interest of scientists from numerous disciplines such as artificial and computational intelligence, neural networks etc. All types of puzzles and games contain their own logic and mathematics. Able to know the science behind them and modelling the logic that a person uses to solve them would shed light to some decisional concepts. This is particularly true from the perspective of computational intelligence. In this paper a logic-based puzzle game called Smashed Sums is considered. The binary integer linear programming formulation is proposed to use in solving and generating the puzzles. Illustrative examples are given to show the validity of the formulation. Some experimental computations are conducted to analyze the puzzle and its complexity. And several open problems are concluded for the further researches.
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    Development of a new hesitant fuzzy ranking model for NTMP ranking problem
    (2021) Atalay, Kumru Didem; Ic, Yusuf Tansel; Kececi, Baris; 0000-0001-9274-7467; AGE-3003-2022
    Nontraditional manufacturing processes (NTMPs) bring the processing capabilities such as machining high strength and hard materials with desired accuracies and surface finish to the manufacturing companies. Therefore, there has been a significant increase in the use and number of NTMPs. Hence, choosing a particular NTMP for a specific application turns out to be a complex decision-making problem, which involves conflicting qualitative and quantitative ranking criteria. In recent NTMP ranking literature, it is noted that fuzzy approaches are better suited for handling uncertainties and incomplete information that exist within the NTMP ranking environment. This paper introduces such a fuzzy approach using the hesitant fuzzy preference selection index (PSI) method for the assessment of the criteria weights and the hesitant fuzzy correlation coefficient principle for ranking and recommending the most appropriate NTMP for a specific application. The proposed methodology and its efficiency in dealing with incomplete information under the fuzzy decision-making environment are explored with a case study. As a result of the study, the proposed model preferred the electron beam machining (EBM) as the most suitable nontraditional manufacturing process. On the other hand, triangular fuzzy TOPSIS methods offered the electrochemical machining (ECM) as the best choice among the alternatives. The differences among the ranking decisions are also analyzed in the paper. It can be concluded from the authors' various applications of the proposed hesitant fuzzy PSI method that it is extremely effective in representing fuzzy decision-making environments in NTMP ranking decisions.