Browsing by Author "Kececi, Baris"

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Development of a Computer Application for Multi-Response Taguchi Optimization
(2016) Ic, Yusuf Tansel; Duran, Hikmet; Kececi, Baris; Ilik, Emrecan; Bilgic, Berkan; 0000-0001-9274-7467; 0000-0002-2730-5993; AGE-3003-2022; F-1639-2011; AAI-1081-2020; AAC-4793-2019; AGQ-5008-2022
In this study, a computer application has been developed for the parameter optimization problem having maximum three quality characteristics and three parameters having three levels for each parameter. When the quality characteristics and the level of the parameters affecting the problem are obtained, appropriate Taguchi array in accordance with an appropriate experimental design is determined by using the developed application. After the collection of the experimental results for the quality characteristics, multi-response optimization problem is converted to single response problem by using the TOPSIS method. In the developed application any parameter design problems having single, two or three quality characteristic can be optimized.
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.
Heterogeneous Vehicle Routing Problem with Simultaneous Pickup and Delivery: Mathematical Formulations and A Heuristic Algorithm
(2015) Kececi, Baris; Altiparmak, Fulya; Kara, Imdat; 0000-0002-2730-5993; AAF-7020-2021; AAC-4793-2019; ABH-1078-2021; F-1639-2011
One of the most important operational decisions in the logistics management is to determine the vehicle routes serving the customers. The Vehicle Routing Problem (VRP) can be defined as the determination of the optimal routes which meet the delivery (or pickup) demands from the depot to the customers. In the real life applications of logistics, vehicles in a fleet may differ from each other. In addition, the requirements arising from customers/goods may reveal the necessity to use different vehicles. Besides, companies do care more about the management of reverse flow of products, semi-finished and raw materials because of their economic benefits and as well as legal and environmental liabilities. In this paper, a variant of the VRP is considered with heterogeneous fleet of vehicles and simultaneous pickup and delivery. This problem is referred to Heterogeneous Vehicle Routing Problem with Simultaneous Pickup and Delivery (HVRPSPD). The HVRPSPD can be defined as determining the routes and the vehicle types on each route while minimizing the total cost. In this paper, a polynomial sized flow-based mathematical model is proposed for the HVRPSPD. Since the HVRPSPD is in the class of NP-hard problems, it is difficult to find the optimal solution in a reasonable time even for the moderate size problems. Therefore, a simple and constructive heuristic algorithm is proposed to solve the medium and large scale HVRPSPD s. This algorithm is the adaptation of very well-known Clarke-Wright Savings approach, which has originally developed for the VRP, to the HVRPSPD. The performances of the proposed mathematical model and the heuristic algorithm have been examined on the test problems.
Inter City Bus Scheduling with Central City Location and Trip Selection
(2020) Guden, Huseyin; Kececi, Baris; Karatas, Mumtaz; Yakici, Ertan; 0000-0002-6287-3216; E-4168-2018
This study considers a real-life inter-city bus scheduling problem that incorporates central city locations and trip selection sub-problems. We seek to determine the size of the bus fleet, the cities to be served, the central cities, and the routes and schedules of buses in the fleet. For this purpose, we developed a number of investment scenarios, and for each scenario, we determined possible trip alternatives between cities and resulting expected profits. We then developed an integer linear programming model and a decomposition-based heuristic, which attempt to solve the problem with the objective of profit maximization Finally, we compare the performance of both solution approaches in terms of the solution quality and computation time for each of the scenarios. The results show that both methods are capable of achieving satisfactory performance for small and medium-size instances, whereas the heuristic outperforms the exact method significantly on large instances.
A Mathematical Formulation And Heuristic Approach For The Heterogeneous Fixed Fleet Vehicle Routing Problem With Simultaneous Pickup And Delivery
(2021) Kececi, Baris; Altiparmak, Fulya; Kara, Imdat; ABH-1078-2021
This study considers a variant of the vehicle routing problem (VRP) called the heterogeneous VRP with simultaneous pickup and delivery (HVRPSPD). The HVRPSPD may broadly be defined as identifying the minimum cost routes and vehicle types. To solve the HVRPSPD, first, we propose a polynomial-size mixed integer programming formulation. Because the HVRPSPD is an NP-hard problem, it is difficult to determine the optimal solution in a reasonable time for moderate and large-size problem instances. Hence, we develop a hybrid metaheuristic approach based on the simulated annealing and local search algorithms called SA-LS. We conduct a computational study in three stages. First, the performance of the mathematical model and SA-LS are investigated on small and medium-size HVRPSPD instances. Second, we compare SA-LS with the constructive heuristics, nearest neigh-borhood and Clarke-Wright savings algorithms, adapted for the HVRPSPD. Finally, the performance of SA-LS is evaluated on the instances of the heterogeneous VRP (HVRP), which is a special case of the HVRPSPD. Computational results demonstrate that the mathematical model can solve small-size instances optimally up to 35 nodes; SA-LS provides good quality solutions for medium and large-size problems. Moreover, SA-LS is superior to simple constructive heuristics and can be a preferable solution method to solve HVRP and VRPSPD instances successfully.
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.
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.
An optimization for milling operation of Kevlar fiber-epoxy composite material using factorial design and goal programming methods
(2019) Ic, Yusuf Tansel; Elaldi, Faruk; Kececi, Baris; Uzun, Gozde Onder; Limoncuoglu, Nur; Aksoy, Irem; 0000-0003-0592-6868; 0000-0002-2730-5993; AAI-1081-2020; AAG-5060-2019; F-1639-2011; AAC-4793-2019
Kevlar fiber-epoxy composite material is extensively used in manufacturing areas because of the advantages of composite material's characteristics. It is usually processed by traditional machining methods but the drawbacks for determination of optimum cutting parameters might cause some material deformations during machining process. In this study, the cutting parameters are concurrently optimized by using the integrated 2k factorial design and goal programming methods for minimum delamination and minimum surface roughness of Kevlar fiber-epoxy composite and the best machining parameters have been obtained for the material. The results were compared with the results of the multi-criteria decision-based Taguchi methods.
Resource Constrained Multi-project Scheduling: Application in Software Company
(2019) Kurt, Pelin Akyil; Kececi, Baris; https://orcid.org/0000-0002-2730-5993
Project scheduling is a common problem of today's companies, which have project type production system. Project scheduling is a mechanism to communicate what tasks need to get done and which organizational resources will be allocated to complete those tasks in what timeframe. In this study, it is aimed to find the shortest completion time of projects and the starting/ending time of each activity as well in a software company, which is running simultaneous projects including multiple activities with predecessors under limited resources. The linear programming formulations in the literature are searched to solve the scheduling problem. The considered model is coded in OPL (Optimization Programming Language). The CPLEX solver engine is used to find the best solution of the coded formulation. In order to facilitate the execution of the project scheduling activities at the company, a computer application in the JAVA programming language is developed. This application also helps to generate the OPL code of the model and as well as to solve the model. In this way, it is possible for the employees to direct the basic scheduling activities more accurately, quickly and efficiently.
Selective generalized travelling salesman problem
(2020) Derya, Tusan; Dinler, Esra; Kececi, Baris; 0000-0002-2730-5993; F-1639-2011
This paper introduces the Selective Generalized Traveling Salesman Problem (SGTSP). In SGTSP, the goal is to determine the maximum profitable tour within the given threshold of the tour's duration, which consists of a subset of clusters and a subset of nodes in each cluster visited on the tour. This problem is a combination of cluster and node selection and determining the shortest path between the selected nodes. We propose eight mixed integer programming (MIP) formulations for SGTSP. All of the given MIP formulations are completely new, which is one of the major novelties of the study. The performance of the proposed formulations is evaluated on a set of test instances by conducting 4608 experimental runs. Overall, 4138 out of 4608 (similar to 90%) test instances were solved optimally by using all formulations.
Topsis Based Taguchi Optimization of Machining Characteristics in End Milling Operation of Kevlar-Epoxy Composites
(2016) Ic, Yusuf Tansel; Elaldi, Faruk; Kececi, Baris; 0000-0001-9274-7467; 0000-0003-0592-6868; 0000-0002-2730-5993; AGE-3003-2022; AAG-5060-2019; AAC-4793-2019
In this study, the surface quality of an end milling operation on Kevlar-epoxy composite material has been investigated. This article presents a study on design of experiment for optimized cutting parameters in the end milling operation of Kevlarepoxy composites using TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) based Taguchi method. In this paper, quality characteristics such as surface roughness and delamination have been selected for evaluation of the milling performance. Four major control parameters namely, feed rate, depth of cut, slope of the cut, and spindle speed have been analyzed for experimentation. From the application of combined TOPSIS-Taguchi method, the optimal combination levels of milling parameters are obtained. It was found that lower feed rate, lower depth of cut, higher slope of cut, and higher spindle speed is desirable for better surface finish.
WEEE estimation and determination of collection points: A case for the Municipality of Cankaya
(2018) Kececi, Baris; Dengiz, Orhan; Dengiz, Berna; Sumer, Emre; Kilic, Aybuke; Ceki, Ece; Inan, Bedia; Cicek, Selda; 0000-0002-2730-5993; F-1639-2011; AAC-4793-2019
Electrical-electronic waste (WEEE) is generated from electric and electronic devices at the end of their lifecycles. When WEEEs are disposed, burned or disassembled for recycling, they are transformed into products containing hazardous substances and harm the environment and human health. Therefore WEEEs should be collected, transported and processed properly during their recycling operations by municipality authority in order to minimize their damage and maximize their economic benefit. In this paper, a study is carried out for the WEEE management of Cankaya Municipality by the cooperation of Environmental Conservation and Control Department of Cankaya. For this purpose first WEEE with a focus on television, refrigerator, washing machine, oven and vacuum cleaner are estimated based on the electronic device usage behavior of residents in Cankaya. Secondly, the WEEE collection points' location problem is solved considering set covering problem.