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Öğe Application of fuzzy optimization to a supply chain network design: A case study of an edible vegetable oils manufacturer(ELSEVIER SCIENCE INC, 2012) Paksoy, Turan; Pehlivan, Nimet Yapici; Ozceylan, ErenThis study applies fuzzy sets to integrate the supply chain network of an edible vegetable oils manufacturer. The proposed fuzzy multi-objective linear programming m attempts to simultaneously minimize the total transportation costs. The first part of total transportation costs is between suppliers and silos; and rest one is between manufacturer and warehouses. The approach incorporates all operating realities and actual patterns at production/distribution network with reference to demands of warehouse capacities of tin and pet packaging lines. The model has been formulated as a multi objective linear programming model where data are modeled by triangular fuzzy numb Finally, the developed fuzzy model is applied for the case study, compiled the re ! and discussed. (C) 2011 Elsevier Inc. All rights reserved.Öğe Fuzzy mathematical programming approaches for reverse supply chain optimization with disassembly line balancing problem(IOS PRESS, 2014) Ozceylan, Eren; Paksoy, TuranToday, the requirement of reverse supply chain (RSC) optimization takes more attention due to environmental and competitive factors. However, increasing attention and existing uncertainty in RSC also increases the difficulties for decisions of production/distribution planning. Therefore, considering strategic and tactical decisions together under fuzziness is being essential. This paper presents a fuzzy programming approach to the integration of RSC optimization (strategic level) and disassembly line balancing (DLB) (tactical level) problems. The aim of this study is to apply fuzzy modeling to optimize a RSC that involves customers, collection/disassembly centers and plants while balancing the disassembly lines in disassembly centers, simultaneously. Two types of fuzzy mathematical programming models with different aggregation operators are used. Finally, accuracy and applicability of the model is illustrated and a comparison of fuzzy approaches is done via a hypothetical example.Öğe Fuzzy Multi Objective Optimization of Green Supply Chain Network(ATLANTIS PRESS, 2011) Paksoy, Turan; Pehlivan, Nimel Yapici; Ozceylan, ErenBecause of the leading environmental disasters, global climate alteration has become one of the most important controversial issues. The greenhouse gas emissions (CO2, methane, etc.) and air pollution increase attention to develop and improve environmental strategies. Thus, environmental sanctions are forcing enterprises to re-consider and re-design supply chain processes in a green way. This paper provides a multi objective model to design a closed-loop supply chain (CLSC) network in a green frame. Our first and second objectives are minimizing the all transportation costs for forward and reverse logistics; third one is minimizing total CO2 emissions; fourth one is encouraging the customers to use recyclable materials as an environmental performance viewpoint. To provide a more realistic modeling by treating the uncertainty in decision maker's objectives, fuzzy modeling is approach is used in this study. The model is explained and tested via fulfilling a numerical example. In scenario analyses, Analytic Hierarchy Process (AHP), fuzzy AHP and fuzzy TOPSIS are applied and compared to evaluate different objectives.Öğe Fuzzy multi-objective linear programming approach for optimising a closed-loop supply chain network(TAYLOR & FRANCIS LTD, 2013) Ozceylan, Eren; Paksoy, TuranWith the urgency of remanufacturing and environmental concerns, closed-loop supply chain (CLSC) networks have drawn the attention of researchers. Although there are many CLSC network models in the literature, most of them do not consider uncertainty in general terms. However, practical situations are often not well defined and thus cannot be described precisely in real world CLSCs. In this paper a mixed integer fuzzy mathematical model is proposed for a CLSC network which includes both forward and reverse flows with multiple periods and multiple parts. A fuzzy multi-objective model (FMOM) approach is applied to take into account the fuzziness in the capacity, objectives, demand constraints and also in the reverse rates. Computational results are presented for a number of scenarios to show and validate applicability and flexibility of the model. Results show that the proposed model presents a systematic framework which enables the logistics manager (LM) to adjust the search direction during the solution procedure to obtain a desired satisfactory solution.Öğe Fuzzy Programming Approach to an Environmental Supply Chain Network Design Problem(OLD CITY PUBLISHING INC, 2015) Ozceylan, Eren; Pehlivan, Nimet Yapici; Paksoy, TuranIncreasing the environmental concerns with legislations and responsibilities are forcing enterprises to take an attention at the impact of their supply chain operations on the environment. An optimally designed supply chain network is required to provide economic, social and environmental requirements in good flows actualizing between suppliers, manufacturers and customers. A nonlinear mixed integer programming model is proposed with the aimed of optimally determining consumed fuel, emitted CO2, driver and transportation costs in this study. However, real world supply chain operations are occurred in a highly dynamic and imprecise environment. Thus, a fuzzy mathematical programming approach is applied to cope with uncertainty in the capacities and demands. The proposed fuzzy model is validated and also compared with different fuzzy mathematical programming approaches through an example, where its applicability is demonstrated for managerial insights.Öğe A genetic algorithm approach for optimising a closed-loop supply chain network with crisp and fuzzy objectives(TAYLOR & FRANCIS LTD, 2014) Demirel, Neslihan; Ozceylan, Eren; Paksoy, Turan; Gokcen, HadiThis paper proposes a mixed integer programming model for a closed-loop supply chain (CLSC) network with multi-periods and multi-parts under two main policies as secondary market pricing and incremental incentive policies. In the first policy, customers order and receive products from distribution centres, but at next period, they can trade among themselves with used products that are returned in a secondary market. Financial incentives are offered to the customers to influence the returns, and the correct amount of collections at different prices is determined by the second policy. In addition to the base case (crisp) formulation, a fuzzy multi-objective extension is applied to solve CLSC network problem with fuzzy objectives to represent vagueness in real-world problems. Then, developed genetic algorithm approach is applied to solve real size crisp and fuzzy CLSC problems. The effectiveness of the proposed meta-heuristic approach is investigated and illustrated by comparing its results with GAMS-CPLEX on a set of crisp/fuzzy problems with different sizes.Öğe A hierarchic approach based on swarm intelligence to solve the traveling salesman problem(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, 2015) Gunduz, Mesut; Kiran, Mustafa Servet; Ozceylan, ErenThe purpose of this paper is to present a new hierarchic method based on swarm intelligence algorithms for solving the well-known traveling salesman problem. The swarm intelligence algorithms implemented in this study are divided into 2 types: path construction-based and path improvement-based methods. The path construction-based method (ant colony optimization (ACO)) produces good solutions but takes more time to achieve a good solution, while the path improvement-based technique (artificial bee colony (ABC)) quickly produces results but does not achieve a good solution in a reasonable time. Therefore, a new hierarchic method, which consists of both ACO and ABC, is proposed to achieve a good solution in a reasonable time. ACO is used to provide a better initial solution for the ABC, which uses the path improvement technique in order to achieve an optimal or near optimal solution. Computational experiments are conducted on 10 instances of well-known data sets available in the literature. The results show that ACO-ABC produces better quality solutions than individual approaches of ACO and ABC with better central processing unit time.Öğe The implications of carbon pricing in Australia: An industrial logistics planning case study(PERGAMON-ELSEVIER SCIENCE LTD, 2013) Fahimnia, Behnam; Reisi, Mohsen; Paksoy, Turan; Ozceylan, ErenThis article investigates the cost implications and carbon reduction potentials of the carbon-pricing scheme in Australia. A non-linear optimization model is developed representing the trade-off between transportation costs and the costs of carbon emission and fuel consumption. The latter are expressed as functions of vehicle traveling speed and road roughness. Piecewise functions and tangent plane, approximation are adopted to linearize the developed model for implementation in CPLEX. Empirical findings from model implementation in an actual case study suggest that the current carbon-pricing scheme in Australia may only make a minor increase in the overall logistics costs that may be inadequate to drive a significant shift in transport behaviors. Crown Copyright (c) 2012 Published by Elsevier Ltd. All rights reserved.Öğe A mixed integer programming model for a closed-loop supply-chain network(TAYLOR & FRANCIS LTD, 2013) Ozceylan, Eren; Paksoy, TuranIn this paper, a new mixed integer mathematical model for a closed-loop supply-chain network that includes both forward and reverse flows with multi-periods and multi-parts is proposed. The proposed model guarantees the optimal values of transportation amounts of manufactured and disassembled products in a closed-loop supply chain while determining the location of plants and retailers. Finally, computational results are presented for a number of scenarios to show and validate the applicability of the model.Öğe Mixed model disassembly line balancing problem with fuzzy goals(TAYLOR & FRANCIS LTD, 2013) Paksoy, Turan; Gungor, Askiner; Ozceylan, Eren; Hancilar, ArifThe collection of used products is the driving force of remanufacturing systems and enterprises can gain significant economic, technical and social benefits from recycling. All products are disassembled up to some level in remanufacturing systems. The best way to disassemble returned products is valid by a well-balanced disassembly line. In this paper, a mixed integer programming (MIP) model is proposed for a mixed model disassembly line balancing (MMDLB) problem with multiple conflicting objectives: (1) minimising the cycle time, (2) minimising the number of disassembly workstations and (3) providing balanced workload per workstation. In most real world MMDLB problems, the targeted goals of decision makers are frequently imprecise or fuzzy because some information may be incomplete and/or unavailable over the planning horizon. This study is the first in the literature to offer the binary fuzzy goal programming (BFGP) and the fuzzy multi-objective programming (FMOP) approaches for the MMDLB problem in order to take into account the vague aspirations of decision makers. An illustrative example based on two industrial products is presented to demonstrate the validity of the proposed models and to compare the performances of the BFGP and the FMOP approaches.Öğe Modeling and optimizing the integrated problem of closed-loop supply chain network design and disassembly line balancing(PERGAMON-ELSEVIER SCIENCE LTD, 2014) Ozceylan, Eren; Paksoy, Turan; Bektas, TolgaThis paper describes an integrated model that jointly optimizes the strategic and tactical decisions of a closed-loop supply chain (CLSC). The strategic level decisions relate to the amounts of goods flowing on the forward and reverse chains. The tactical level decisions concern balancing disassembly lines in the reverse chain. The objective is to minimize costs of transportation, purchasing, refurbishing, and operating the disassembly workstations. A nonlinear mixed integer programming formulation is described for the problem. Numerical examples are presented using the proposed model. (C) 2013 Elsevier Ltd. All rights reserved.Öğe A New Trade-off Model for Fuzzy Supply Chain Network Design and Optimization(ATLANTIS PRESS, 2011) Paksoy, Turan; Pehlivan, Nimet Yapici; Ozceylan, ErenThis problem includes fuzzy parameters, choosing suppliers according to their quality raw materials and supplier contracts. There is a trade-off between raw material quality, its purchasing and reprocessing costs. If decision maker (DM) wishes to work with a supplier which supplies a low quality raw material, this raw material can be in need of reprocessing. To avoid the reprocessing costs, a supplier which serves a high quality raw material can be chosen but at this time the DM has to face a high purchasing cost. An integrated fuzzy supply chain network system is considered to accomplish problems aforementioned trade-offs above.Öğe A New Tradeoff Model for Fuzzy Supply Chain Network Design and Optimization(TAYLOR & FRANCIS INC, 2013) Paksoy, Turan; Pehlivan, Nimet Yapici; Ozceylan, ErenThis article proposes a novel mixed integer linear programming model for solving a fuzzy supply chain network (SCN) design problem. This problem includes fuzzy parameters, choosing suppliers according to their quality of raw materials, and the supplier's engagement contracts. There is a tradeoff between raw material quality, and its purchasing and reprocessing costs. If a decision-maker (DM) wishes to work with a supplier that supplies a low-quality raw material, this raw material may be in need of reprocessing. To avoid the reprocessing costs, a supplier that provides a high-quality raw material can be chosen, but in this case the DM faces a high purchasing cost. An integrated fuzzy SCN system that consists of multiple suppliers, manufacturers, distribution centers, and retailers is considered in order to address problems under the aforementioned tradeoffs. Finally, concluding remarks and suggestions for future work are presented.Öğe A novel hybrid approach based on Particle Swarm Optimization and Ant Colony Algorithm to forecast energy demand of Turkey(PERGAMON-ELSEVIER SCIENCE LTD, 2012) Kiran, Mustafa Servet; Ozceylan, Eren; Gunduz, Mesut; Paksoy, TuranThis paper proposes a new hybrid method (HAP) for estimating energy demand of Turkey using Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). Proposed energy demand model (HAPE) is the first model which integrates two mentioned meta-heuristic techniques. While, PSO, developed for solving continuous optimization problems, is a population based stochastic technique; ACO, simulating behaviors between nest and food source of real ants, is generally used for discrete optimizations. Hybrid method based PSO and ACO is developed to estimate energy demand using gross domestic product (GDP), population, import and export. HAPE is developed in two forms which are linear (HAPEL) and quadratic (HAPEQ). The future energy demand is estimated under different scenarios. In order to show the accuracy of the algorithm, a comparison is made with ACO and PSO which are developed for the same problem. According to obtained results, relative estimation errors of the HAPE model are the lowest of them and quadratic form (HAPEQ) provides better-fit solutions due to fluctuations of the socio-economic indicators. (C) 2011 Elsevier Ltd. All rights reserved.Öğe Operational and environmental performance measures in a multi-product closed-loop supply chain(PERGAMON-ELSEVIER SCIENCE LTD, 2011) Paksoy, Turan; Bektas, Tolga; Ozceylan, ErenThis paper investigates a number of operational and environmental performance measures, in particular those related to transportation operations, within a closed-loop supply chain. A mathematical model in the form of a linear programming formulation is used to model the problem, which captures the trade-offs between various costs, including those of emissions and of transporting commodities within the chain. Computational results are presented for a number of scenarios. using a realistic network instance. (C) 2010 Elsevier Ltd. All rights reserved.Öğe Profit oriented supply chain network optimization(SPRINGER, 2013) Paksoy, Turan; Ozceylan, Eren; Weber, Gerhard-WilhelmThis paper proposes a novel mixed integer linear programming model to solve a supply chain network design problem. The proposed model deals with major issues for supply chains; product quality and cost. These issues are usually solved separately, but in this paper, we investigate effects of product quality on supply chain design and transportation flow. A trade-off between raw material quality, its purchasing and reprocessing costs was considered. Assuming decision maker (DM) wishes to work with a supplier which serves a low quality raw material; this raw material should be in need of reprocessing. To avoid the reprocessing costs, a supplier which serves a high quality raw material should be chosen but at this time the DM has to face a high purchasing cost. A supply chain network which consists of multiple suppliers, manufacturers, distribution centers and retailers is tried to be designed to accomplish aforementioned above trade-offs. The paper examines and discusses the relationship between product quality and supply chain design and offers several managerial insights.Öğe Reverse supply chain optimisation with disassembly line balancing(TAYLOR & FRANCIS LTD, 2013) Ozceylan, Eren; Paksoy, TuranDue to responding environmental issues, conforming governmental legislations and providing economic benefits, there has been a growing interest in recycling activities through the supply chains. Reverse supply chain (RSC) optimisation problem has a great potential as an efficient tactic to achieve this goal. While disassembly, one of the main activities in RSC, enables reuse and recycling of products and prevents the overuse, disassembly line balancing problem involves determination of a line design in which used products are partially/completely disassembled to obtain available components. The aim of this study is to optimise a RSC, involving customers, collection/disassembly centres and plants, that minimises the transportation costs while balancing the disassembly lines, which minimises the total fixed costs of opened workstations, simultaneously. A non-linear mixed-integer programming model, which simultaneously determines: (i) optimal distribution between the facilities with minimum cost, (ii) the number of disassembly workstations that will be opened with minimum cost, (iii) the cycle time in each disassembly centre and (iv) optimal assignment of tasks to workstations, is developed. A numerical example is given to illustrate the applicability of the proposed model. Different scenarios have been conducted to show the effects of sensitivity analyses on the performance measures of the problem.Öğe Supply chain optimisation with U-type assembly line balancing(TAYLOR & FRANCIS LTD, 2012) Paksoy, Turan; Ozceylan, ErenIn supply chain optimisation problems, determining the location and number of facilities is considered at a strategic level, while mid-term and short-term decisions such as those concerning assembly policy, inventory levels, lot sizes and scheduling are handled at the tactical and operational levels. However, considering these decisions simultaneously is almost always ignored during the optimisation of distribution/production processes. The aim of the study is to optimise the supply chain network (strategic level), including manufacturers, assemblers and customers, while simultaneously balancing the U-type assembly lines (tactical level) in assemblers. A nonlinear mixed integer mathematical model is proposed to minimise the total costs and the number of assembly stations while minimising the total fixed costs of stations. To show the validity and usefulness of the proposed model, a numerical example with different scenarios and sensitivity analyses is given and discussed.Öğe Swarm intelligence approaches to estimate electricity energy demand in Turkey(ELSEVIER SCIENCE BV, 2012) Kiran, Mustafa Servet; Ozceylan, Eren; Gunduz, Mesut; Paksoy, TuranThis paper proposes two new models based on artificial bee colony (ABC) and particle swarm optimization (PSO) techniques to estimate electricity energy demand in Turkey. ABC and PSO electricity energy estimation models (ABCEE and PSOEE) are developed by incorporating gross domestic product (GDP), population, import and export figures of Turkey as inputs. All models are proposed in two forms, linear and quadratic. Also different neighbor selection mechanisms are attempted for ABCEE model to increase convergence to minimum of the algorithm. In order to indicate the applicability and accuracy of the proposed models, a comparison is made with ant colony optimization (ACO) which is available for the same problem in the literature. According to obtained results, relative estimation errors of the proposed models are lower than ACO and quadratic form provides better-fit solutions than linear form due to fluctuations of the socio-economic indicators. Finally, Turkey's electricity energy demand is projected until 2025 according to three different scenarios. (C) 2012 Elsevier B.V. All rights reserved.
