Browsing by Author "Yuksel, Damla"

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Citation - WoS: 8
Citation - Scopus: 11
A Discrete Artificial Bee Colony Algorithm for the Energy-Efficient No-Wait Flowshop Scheduling Problem
(ELSEVIER SCIENCE BV, 2019) M. Fatih Tasgetiren; Damla Yuksel; Liang Gao; Quan-Ke Pan; Peigen Li; Yuksel, Damla; Tasgetiren, M. Fatih; Gao, Liang; Li, Peigen; Fatih Tasgetiren, M.; Pan, Quan-Ke; CH Dagli; GA Suer
No-wait permutation flow shop scheduling problem (NWPFSP) is a variant of permutation flow shop scheduling problem (PFSP) where the processing of each job must be continuous from start to end without any interruption. That is once a job starts its processing it has to be processed until the last machine without any interruption. The aim of this study is to propose an energy-efficient NWPFSP for the determination of a trade-off between total flow time and total energy consumption by obtaining the Pareto optimal set that is the non-dominated solution set. A bi-objective mixed-integer programming model is developed where the machines can operate at different speed levels. Since the problem is NP-complete an energy-efficient discrete artificial bee colony (DABC) and an energy-efficient genetic algorithm (MOGA) also a variant of this algorithm (MOGALS) are developed as heuristic methods. First the performance of these algorithms for comparison with the mathematical model is represented in small size instances in the scope of cardinality and quality of the non-dominated solutions then it is shown that DABC performs better than two other algorithms in larger instances. (C) 2019 The Authors. Published by Elsevier Ltd.
Citation - WoS: 1
A Discrete-Time Resource Allocated Project Scheduling Model
(Springer Science and Business Media Deutschland GmbH, 2022) Berkay Çataltuğ; Helin Su Çorapcı; Levent Kandiller; Fatih Kağan Keremit; Giray Bingöl Kırbaş; Özge Ötleş; Atakan Özerkan; Hazal Tucu; Damla Yüksel; Yuksel, Damla; Cataltug, Berkay; Corapci, Helin Su; Keremit, Fatih Kagan; Otles, Ozge; Kirbas, Giray Bingol; Kandiller, Levent; N.M. Durakbasa , M.G. Gençyılmaz
Project Management involves the implementation of knowledge and skills to meet project requirements with beneficial tools and techniques. Project Management consists of tools that provide improvement in the pillars of time cost and quality. Discrete-Time Resource Allocated Project Scheduling Model (DTRAPS) is developed to minimize time to maximize quality and to minimize the cost of a project together in one tool. By means of this tool it is possible to allocate the resources over the project tasks in an optimized way with respect to each pillar of the triangle. Moreover sensitivity analysis on the model is done with the number of activities resource number and available time window parameters. The results indicate that the model is robust. Since the model is taking a longer CPU time in solving large problems heuristics such as Greedy Smallest Requirements First (SRF) Largest Requirements First (LRF) and Randomized are developed together with Swap improvement algorithm. Heuristics are compared and analyzed. Last of all a dynamic and user-friendly decision support system is developed on Excel-VBA for the model solution via CPLEX solver and heuristics. © 2022 Elsevier B.V. All rights reserved.
Citation - WoS: 48
Citation - Scopus: 61
A Green Dual-Channel Closed-Loop Supply Chain Network Design Model
(ELSEVIER SCI LTD, 2022) Yigit Kazancoglu; Damla Yuksel; Muruvvet Deniz Sezer; Sachin Kumar Mangla; Lianlian Hua; Yuksel, Damla; Sezer, Muruvvet Deniz; Hua, Lianlian; Kazancoglu, Yigit; Mangla, Sachin Kumar
Environmental considerations have become a significant issue in the design of supply chain networks due to today's increasing globalization trends. Therefore supply chain network design needs to be managed in an efficient way to deal with the complex networks involved. The aim of this article is to present a multi-objective optimization model for a green dual-channel supply chain network that handles economic and environmental objectives to optimize network flow. A complex mixed-integer linear programming model (MILP) has been proposed in a green dual-channel and closed-loop supply chain (CLSC) network design. The main objective of the generated MILP model is to investigate the optimal selection of echelons and the optimal selection of transportation alternatives between these echelons in a CLSC network that includes an e-commerce channel structure based on economic and environmental considerations. Environmental aims are achieved by decreasing CO2 emissions and by reducing PM (particulate matter) concentration throughout the network. In addition economic aims are also met by minimizing the overall cost. The validity of the presented model is supported by a case study in the home appliances industry. The results indicate that this model provides valuable knowledge and various alternatives to managers and policymakers depending on the different weight combinations.
Citation - WoS: 2
A multiphase acceptance sampling model by attributes to investigate the production interruptions in batch production within tobacco industry
(EMERALD GROUP PUBLISHING LTD, 2022) Damla Yuksel; Yigit Kazancoglu; P. R. S. Sarma; Yuksel, Damla; Kazancoglu, Yigit; Sarma, P. R. S.
Purpose This paper aims to create a new decision-making procedure that uses Lot-by-Lot Acceptance Sampling Plan by Attributes methodology in the production processes when any production interruption is observed in tobacco industry which is a significant example of batch production. Design/methodology/approach Based on the fish bone diagram the reasons of the production interruptions are categorized then Lot-by-Lot Acceptance Sampling Plan by Attributes is studied to overcome the reasons of the production interruptions. Furthermore managerial aspects of decision making are not ignored and hence acceptance sampling models are determined by an Analytical Hierarchy Process (AHP) among the alternative acceptance sampling models. Findings A three-phased acceptance sampling model is generated for determination of the reasons of production interruptions. Hence the necessary actions are provided according to the results of the proposed acceptance sampling model. Initially 729 alternative acceptance sampling models are found and 38 of them are chosen by relaxation. Then five acceptance sampling models are determined by AHP. Practical implications The current experience dependent decision mechanism is suggested to be replaced by the proposed acceptance sampling model which is based on both statistical and managerial decision-making procedure. Originality/value Acceptance sampling plans are considered as a decision-making procedure for various cases in production processes. However to the best of our knowledge Lot-by-Lot Acceptance Sampling Plan by Attributes has not been considered as a decision-making procedure for batch production when any production interruption is investigated.
Citation - WoS: 1
Citation - Scopus: 2
Intelligent Valid Inequalities for No-Wait Permutation Flowshop Scheduling Problems
(Springer Science and Business Media Deutschland GmbH, 2022) Damla Yüksel; Levent Kandiller; M. Fatih Tasgetiren; Yuksel, Damla; Tasgetiren, Mehmet Fatih; Kandiller, Levent; C. Kahraman , S. Cevik Onar , B. Oztaysi , I.U. Sari , A.C. Tolga , S. Cebi
The no-wait permutation flowshop scheduling problem is a well-recognized scheduling problem. Examples can be encountered in several industries such as hot metal rolling painting chemical steel industries etc. In this flowshop setting the jobs are not allowed to wait between consecutive machines. Owing to the NP-hardness identity of the problem the developed mathematical models to solve this problem cannot reach optimal solutions for large instances in polynomial time. However the quality of the objective functions and the gap values obtained by the mathematical models in a specific time window can be improved by valid inequalities. This study generates intelligent valid inequalities to improve a mathematical model’s performance in optimizing the no-wait permutation flow shop scheduling problems. Valid inequalities’ performance is tested for three significant objective functions: (i) makespan (ii) total flow time and (iii) total tardiness. According to the computational experiments the new valid inequalities improve the outcomes of the mathematical models mostly in the way of the gap values for makespan total flow time and total tardiness objective criteria. © 2022 Elsevier B.V. All rights reserved.
Citation - Scopus: 9
Metaheuristics for Energy-Efficient No-Wait Flowshops: A Trade-off Between Makespan and Total Energy Consumption
(IEEE, 2020) Damla Yuksel; Mehmet Fatih Tasgetiren; Levent Kandiller; Quan-Ke Pan; Yuksel, Damla; Tasgetiren, Mehmet Fatih; Kandiller, Levent; Pan, Quan-Ke
No-wait flowshop scheduling problem (NWFSP) is a well-known strongly NP-hard problem where in-process waiting is not allowed between any two consecutive machines in such a way that once a job is started subsequent processing must be carried out on all machines until completion. In this paper we propose an energy-efficient NWFSP in order to investigate the trade-off between makespan and total energy consumption. The energy-efficient NWFSP aims to seek to obtain Pareto solution sets to minimize the makespan and the total energy consumption conflicting with each other. Unlike the classical NWFSP there are different speed levels for each job on machines and the processing times of jobs can differ according to the assigned speed levels. Therefore we modify the formulation of NWFSP by introducing a speed scaling strategy in order to approximate Pareto solution sets i.e. non-dominated solution sets. In this paper we propose a mixed-integer linear programming model (MILP) an energy-efficient variable block insertion heuristic (EE-VBIH) an energy-efficient iterated greedy algorithm (IG) and an energy-efficient & IG-ALL) to solve the energy-efficient NWFSP. Extensive computational analyses on Taillard's benchmark suite show that the proposed algorithms are very effective for approximating Pareto solution sets.