Endüstri Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://gcris.khas.edu.tr/handle/20.500.12469/48

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Citation Count: 4
Agent-based Optimization to Estimate Nash Equilibrium in Power Markets
(Taylor & Francis Inc, 2013) Yücekaya, Ahmet; Valenzuela, Jorge
In most deregulated power markets firms bid daily into a day-ahead power market. The auction mechanism supply and demand determine the equilibrium at each hour. In this environment firms aim to maximize their revenues by carefully determining their bids. This requires the development of effective computational methods that help them estimate their competitors' behaviors under incomplete information. In this article an agent-based method that uses particle swarm optimization is described to simulate the behavior of market participants. Particle swarm optimization is used in the bidding process and an agent-based model is applied to find a Nash equilibrium. Different stopping conditions are used to determine the equilibrium. Experimental results are presented for two power systems.
Citation Count: 5
An analysis of price spikes and deviations in the deregulated Turkish power market
(Elsevier, 2019) Bilge, Ayşe Hümeyra; Yücekaya, Ahmet; Bilge, Ayşe Hümeyra
The successful operation of a real time market is related to the planning in the day ahead market. We analyze the day ahead and real time market data for the Turkish power market for the period 2012-2015 to classify price spikes and their causes. We also focus on the levels of deviation between the day ahead market values and the real time market values. We define price deviation and load deviation ratios to measure the level of deviation both in price and demand. The analysis for the load is based on load shedding and cycling values. We analyze the mean and standard deviation in market prices and we determine the price spike as a two sigma deviation from the mean value. It is shown that 60% of the price deviation ratios are in the range of ( +/- 20%), while 44% are in the range of ( +/- 10%) and 35% are in the range of (+/- 5%). We also show that 56.9% of the spikes are due to problems in the generation of natural gas based power plants which affect the day ahead and real time prices. A total of 29.2% of the spikes are due to power plant and system failures that affect only real time prices. The share of high temperature based spikes is 13.9% which is a result of air conditioner usage.
Citation Count: 1
An approach to evaluate CAM software alternatives
(TAYLOR & FRANCIS LTD, 2020) Ayağ, Zeki
The selection process for the best computer-aided manufacturing (CAM) software among a set of potential number of alternatives in market has been critical issue for most companies that aim to make their design/manufacturing-related activities automated. Because this selection process is very vital for companies because a wrong decision might put them into a difficult position in terms of economical, market share and time spent. Therefore, today's companies have used different multiple-criteria decision making (MCDM) methods for the evaluation study of CAM software alternatives to make this complex process easily applicable and not time-consuming. Among the MCDM methods in literature, the analytic hierarchy process (AHP) method has been widely used for various MCDM problems in both academic researches and industrial practices. However, in some cases, because of the vagueness and uncertainty on the judgments of decision maker(s), the crisp pair wise comparison in the conventional AHP seems to be insufficient and imprecise to capture the right judgments of decision maker(s). Therefore, a fuzzy logic method is integrated in the pair wise comparison of AHP to make up for this deficiency in the conventional AHP, called as fuzzy AHP. Moreover, the proposed approach is also realized on a case study.
Citation Count: 5
Assortment optimization with log-linear demand: Application at a Turkish grocery store
(Elsevier, 2019) Hekimoğlu, Mustafa; Sevim, İsmail; Aksezer, Çağlar Sezgin; Durmuş, İpek
In retail sector product variety increases faster than shelf spaces of retail stores where goods are presented to consumers. Hence assortment planning is an important task for sustained financial success of a retailer in a competitive business environment. In this study we consider the assortment planning problem of a retailer in Turkey. Using empirical point-of-sale data a demand model is developed and utilized in the optimization model. Due to nonlinear nature of the model and integrality constraint we find that it is difficult to obtain a solution even for moderately large product sets. We propose a greedy heuristic approach that generates better results than the mixed integer nonlinear programming in a reasonably shorter period of time for medium and large problem sizes. We also proved that our method has a worst-case time complexity of O(n 2 )while other two well-known heuristics’ complexities are O(n 3 )and O(n 4 ). Also numerical experiments reveal that our method has a better performance than the worst-case as it generates better results in a much shorter run-times compared to other methods. © 2019 Elsevier Ltd
Citation Count: 0
Babbling through social media: A cross-country study mapping out social networks using eWOM intentions
(Springer, 2023) Zülal, İşler; Kıygı-Çallı, Meltem; El Oraiby, Maryam
This research aims to determine the factors affecting the users’ electronic word-of-mouth (eWOM) seeking and sharing intentions and to reveal the interactions among and within clusters using social network analysis (SNA). This study includes three hierarchical sub-studies conducted in two countries, Turkey and Poland. First, we develop a segmentation for social networking site (SNS) users based on the frequency of sharing product-related information on SNSs. Second, we investigate the impact of several factors that affect eWOM seeking and sharing intentions using regression analysis. In the second sub-study, we also include the identified segments developed in the first sub-study as another factor that may have differentiated eWOM intentions. Third, to understand the degree of interaction among SNS users, we apply an SNA using the forecasted eWOM intentions scores from the second sub-study, which gives us hypothetical social networks. The results of SNA present strong interactions inter- and intra-clusters in both countries. Some key findings include the identification of three SNS user segments, including “Middlers,” that may be of particular interest to brands. We also find that in terms of eWOM intentions, users in Turkey are more active than in Poland. Although some predictors of eWOM seeking and sharing intentions differ between the two countries, users intend to be more active in eWOM seeking than in eWOM sharing. The comparative study provides valuable insights for decision-makers to engage different market segments via SNSs with various proposed features using suggested information contents for selected product categories.
Citation Count: 11
Bidding of price taker power generators in the deregulated Turkish power market
(Pergamon-Elsevier Science Ltd, 2013) Yücekaya, Ahmet; Yücekaya, Ahmet
In deregulated power markets power firms bid into the day-ahead power market either with buy offers or sell offers. The auction mechanism and competition determine the equilibrium price and quantity for each hour. If the bid price of a company is below the market clearing price then the offer of the company is accepted and rewarded with the market price. A company can be a price maker or price taker depending on the capacity it offers to the market. A price-taker unit must determine the right offer that will maximize their profit given price uncertainty and blind auction rules. This paper first examines power supply in the Turkish electricity market and bidding process. Then a marginal cost-based Monte Carlo method is developed to determine hourly and block bidding strategies of price taker units. Historical market prices are then implemented in a normal distribution to generate hourly price scenarios. A solution methodology is developed that maximizes the expected profit of each hourly and block bidding strategy over price scenarios. The generator is able to both evaluate the hourly bidding and block bidding strategies and find the best bidding strategy that will be submitted to the market using the proposed methodology. The model is illustrated for two coal units in Turkish power market and the results are presented. (C) 2013 Elsevier Ltd. All rights reserved.
Citation Count: 0
Canonical forms for families of anti-commuting diagonalizable linear operators
(Elsevier Science Inc, 2012) Bilge, Ayşe Hümeyra; Bilge, Ayşe Hümeyra
It is well known that a commuting family of diagonalizable linear operators on a finite dimensional vector space is simultaneously diagonalizable. In this paper we consider a family A = {A(a)} A(a) : V -> V a = 1... N of anti-commuting (complex) linear operators on a finite dimensional vector space. We prove that if the family is diagonalizable over the complex numbers then V has an A-invariant direct sum decomposition into subspaces V(alpha) such that the restriction of the family A to V(alpha) is a representation of a Clifford algebra. Thus unlike the families of commuting diagonalizable operators diagonalizable anti-commuting families cannot be simultaneously digonalized but on each subspace they can be put simultaneously to (non-unique) canonical forms. The construction of canonical forms for complex representations is straightforward while for the real representations it follows from the results of [A.H. Bilge S. Kocak S. Uguz Canonical bases for real representations of Clifford algebras Linear Algebra Appl. 419 (2006) 417-439]. (C) 2011 Elsevier Inc. All rights reserved.
Citation Count: 39
Computing trade-offs in robust design: Perspectives of the mean squared error
(Pergamon-Elsevier Science Ltd, 2011) Samanlıoğlu, Funda; Samanlıoğlu, Funda; Cho, Byung Rae; Wiecek, Margaret M.
Researchers often identify robust design as one of the most effective engineering design methods for continuous quality improvement. When more than one quality characteristic is considered an important question is how to trade off robust design solutions. In this paper we consider a bi-objective robust design problem for which Pareto solutions of two quality characteristics need to be obtained. In practical robust design applications a second-order polynomial model is adequate to accommodate the curvature of process mean and variance functions thus mean-squared robust design models frequently used by many researchers would contain fourth-order terms. Consequently the associated Pareto frontier might be non-convex and supported and non-supported efficient solutions needs to be generated. So the objective of this paper is to develop a lexicographic weighted-Tchebycheff based bi-objective robust design model to generate the associated Pareto frontier. Our numerical example clearly shows the advantages of this model over frequently used weighted-sums model. (C) 2010 Elsevier Ltd. All rights reserved.
Citation Count: 22
Demand Uncertainty And Inventory Turnover Performance An Empirical Analysis of the US Retail Industry
(Emerald Group Publishing Limited, 2016) Hancerliogullari, Gulsah; Sen, Alper; Aktunç, Esra Ağca
Purpose - The purpose of this paper is to investigate the impact of demand uncertainty on inventory turnover performance through empirical modeling. In particular the authors use the inaccuracy of quarterly sales forecasts as a proxy for demand uncertainty and study its impact on firm-level inventory turnover ratios. Design/methodology/approach - The authors use regression analysis to study the effect of various measures on inventory performance. The authors use a sample financial data for 304 publicly listed US retail firms for the 25-year period from 1985 to 2009. Findings - Controlling for the effects of retail segments and year it is found that inventory turnover is negatively correlated with mean absolute percentage error of quarterly sales forecasts and gross margin and positively correlated with capital intensity and sales surprise. These four variables explain 73.7 percent of the variation across firms and over time and 93.4 percent of the within-firm variation in the data. Practical implications - In addition to conducting an empirical investigation for the sources of variation in a major operational metric the results in this study can also be used to benchmark a retailer's inventory performance against its competitors. Originality/value - The authors develop a new proxy to measure the demand uncertainty that a firm faces and show that this measure may help to explain the variation in inventory performance.
Citation Count: 80
Effects of cylinder Reynolds number on the turbulent horseshoe vortex system and near wake of a surface-mounted circular cylinder
(Amer Inst Physics, 2015) Kirkil, Gökhan; Constantinescu, George
The turbulent horseshoe vortex (HV) system and the near-wake flow past a circular cylinder mounted on a flat bed in an open channel are investigated based on the results of eddy-resolving simulations and supporting flow visualizations. Of particular interest are the changes in the mean flow and turbulence statistics within the HV region as the necklace vortices wrap around the cylinder's base and the variation of the mean flow and turbulence statistics in the near wake in between the channel bed and the free surface. While it is well known that the drag crisis induces important changes in the flow past infinitely long circular cylinders the changes are less understood and more complex for the case of flow past a surface-mounted cylinder. This is because even at very high cylinder Reynolds numbers Re-D the flow regime remains subcritical in the vicinity of the bed surface due to the reduction of the incoming flow velocity within the bottom boundary layer. The paper provides a detailed discussion of the changes in the flow physics between cylinder Reynolds numbers at which the flow in the upstream part of the separated shear layers (SSLs) is laminar (Re-D = 16 000 subcritical flow regime) and Reynolds numbers at which the transition occurs inside the attached boundary layers away from the bed and the flow within the SSLs is turbulent (Re-D = 5 * 10(5) supercritical flow regime). The changes between the two regimes in the dynamics and level of coherence of the large-scale coherent structures (necklace vortices vortex tubes shed in the SSLs and roller vortices shed in the wake) and their capacity to induce high-magnitude bed friction velocities in the mean and instantaneous flow fields and to amplify the near-bed turbulence are analyzed. Being able to quantitatively and qualitatively describe these changes is critical to understand Reynolds-number-induced scale effects on sediment erosion mechanisms around cylinders mounted on a loose bed which is a problem of great practical relevance (e.g. for pier scour studies). (C) 2015 AIP Publishing LLC.
Citation Count: 2
Efficient approaches for furnace loading of cylindrical parts
(Elsevier Science Inc, 2014) Samanlıoğlu, Funda; Ram, Bala; Samanlıoğlu, Funda
This paper addresses the heat treatment operation in a manufacturing plant that produces different types of cylindrical parts. The immediate prior process to heat treatment is furnace-loading where parts are loaded into baskets. The furnace-loading process is complex and involves issues relating to geometry and heterogeneity in the parts and in their processing requirements. Currently furnace-loading is accomplished by operator ingenuity ; consequently the parts loaded in heat treatment often do not use furnace capacity adequately. Efficiency in furnace operation can be achieved by improving basket utilization which is determined by the furnace-loading process. This paper describes the development of integer and mixed integer LP models for 3D loading of cylindrical parts into furnace baskets. The models consider the exact location of parts to be loaded on the basket and incorporate three models with different objectives ; the first addresses the nesting of parts within one another the second addresses the number of basket layers used and the third addresses the number of baskets used. (C) 2013 Elsevier Inc. All rights reserved.
Citation Count: 2
An equivalence class decomposition of finite metric spaces via Gromov products
(Elsevier Science Bv, 2017) Bilge, Ayşe Hümeyra; Çelik, Derya; Koçak, Şahin
Let (X, d) be a finite metric space with elements P-i, i = 1,..., n and with the distance functions d(ij) The Gromov Product of the "triangle" (P-i, P-j, P-k) with vertices P-t, P-j and P-k at the vertex Pi is defined by Delta(ijk) = 1/2(d(ij) + d(ik) - d(jk)). We show that the collection of Gromov products determines the metric. We call a metric space Delta-generic, if the set of all Gromov products at a fixed vertex P-i has a unique smallest element (for i = 1,., n). We consider the function assigning to each vertex P-i the edge {P-i, P-k} of the triangle (P-i, P-j, P-k) realizing the minimal Gromov product at P-i and we call this function the Gromov product structure of the metric space (X, d). We say two Delta-generic metric spaces (X, d) and (X, d') to be Gromov product equivalent, if the corresponding Gromov product structures are the same up to a permutation of X. For n = 3, 4 there is one (Delta-generic) Gromov equivalence class and for n = 5 there are three (Delta-generic) Gromov equivalence classes. For n = 6 we show by computer that there are 26 distinct (Delta-generic) Gromov equivalence classes. (C) 2017 Elsevier B.V. All rights reserved.
Citation Count: 65
Evaluating machine tool alternatives through modified TOPSIS and alpha-cut based fuzzy ANP
(Elsevier Science Bv, 2012) Ayağ, Zeki; Özdemir, Rıfat Gürcan
The problem of machine tool selection among available alternatives has been critical issue for most companies in fast-growing markets for a long time. In the presence of many alternatives and selection criteria the problem becomes a multiple-criteria decision making (MCDM) machine tool selection problem. Therefore most companies have utilized various methods to successfully carry out this difficult and time-consuming process. In this work both of the most used MCDM methods the modified TOPSIS and the Analytical Network Process (ANP) are introduced to present a performance analysis on machine tool selection problem. The ANP method is used to determine the relative weights of a set of the evaluation criteria as the modified TOPSIS method is utilized to rank competing machine tool alternatives in terms of their overall performance. Furthermore in this paper we use a fuzzy extension of ANP a more general form of AHP which uses uncertain human preferences as input information in the decision-making process because AHP cannot accommodate the variety of interactions dependencies and feedback between higher and lower level elements. Instead of using the classical eigenvector prioritization method in AHP only employed in the prioritization stage of ANP a fuzzy logic method providing more accuracy on judgments is applied. The resulting fuzzy ANP enhances the potential of the conventional ANP for dealing with imprecise and uncertain human comparison judgments. The proposed approach is also applied for a real-life case in a company. (C) 2012 Elsevier B.V. All rights reserved.
Citation Count: 21
Evaluation Of Water Supply Alternatives For Istanbul Using Forecasting And Multi-Criteria Decision Making Methods
(Elsevier Ltd, 2020) Hekimoğlu, Mustafa; Erbay, Barbaros; Hekimoğlu, Mustafa; Burak, Selmin
Water scarcity is one of the most serious problems of the future due to increasing urbanization and water demand. Urban water planners need to balance increasing water demand with water resources that are under increasing pressure due to climate change and water pollution. Decision makers are forced to select the most appropriate water management alternative with respect to multiple, conflicting criteria based on short and long term projections of water demand in the future. In this paper, we consider water management in Istanbul, a megacity with a population of 15 million. Purpose: The purpose of this paper is to develop a method combining demand forecasting with multi-criteria decision making (MCDM) methods to evaluate five different water supply alternatives with respect to seven criteria using opinions of experts and stakeholders from different sectors. Methodology: To combine forecasting with MCDM, we design a data collection method in which we share our demand forecasts with our experts. For demand forecasting, we compare Holt-Winters, Seasonal Autoregressive Integrated Moving Average (S-ARIMA), and feedforward Artificial Neural Network (ANN) models and select S-ARIMA as the best forecasting model for monthly water consumption data. Generated demand projections are shared with experts from different sectors and collected data is evaluated with Fuzzy Theory using two distinct MCDM models: Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE). Also our analyses are complemented with two sensitivity analyses. Findings: Our results indicate that greywater reuse is the best alternative to satisfy the growing water demand of the city whereas all experts find desalination and inter-basin water transfer as the least attractive solutions. In addition, we adopt the PROMETHEE GDSS procedure to obtain a GAIA plane indicating consensus among experts. Furthermore, we find that our results are moderately sensitive to the number of experts and they are insensitive to changes in experts’ evaluations. Novelty: To the best of our knowledge, our study is the first one incorporating water demand and supply management concepts into the evaluation of alternatives. From a methodological perspective, water demand projections have never been used in an MCDM study in the literature. Also, this paper contributes to the literature with a mathematical construction of consensus and Monte Carlo simulations for the sufficiency of experts consulted in a study.
Citation Count: 3
An evolutionary approach for tuning parametric Esau and Williams heuristics
(Palgrave Macmillan Ltd., 2012) Battarra, Maria; Oncan, Temel; Altinel, I. Kuban; Golden, Bruce; Vigo, Daniele; Phillips, E.
Owing to its inherent difficulty many heuristic solution methods have been proposed for the capacitated minimum spanning tree problem. On the basis of recent developments it is clear that the best metaheuristic implementations outperform classical heuristics. Unfortunately they require long computing times and may not be very easy to implement which explains the popularity of the Esau and Williams heuristic in practice and the motivation behind its enhancements. Some of these enhancements involve parameters and their accuracy becomes nearly competitive with the best metaheuristics when they are tuned properly which is usually done using a grid search within given search intervals for the parameters. In this work we propose a genetic algorithm parameter setting procedure. Computational results show that the new method is even more accurate than an enumerative approach and much more efficient. Journal of the Operational Research Society (2012) 63 368-378. doi:10.1057/jors.2011.36 Published online 1 June 2011
Citation Count: 68
Forecasting electricity demand for Turkey: Modeling periodic variations and demand segregation
(Elsevier, 2017) Bilge, Ayşe Hümeyra; Yücekaya, Ahmet; Bilge, Ayşe Hümeyra
In deregulated electricity markets the independent system operator (ISO) oversees the power system and manages the supply and demand balancing process. In a typical day the ISO announces the electricity demand forecast for the next day and gives participants an option to prepare offers to meet the demand. In order to have a reliable power system and successful market operation it is crucial to estimate the electricity demand accurately. In this paper we develop an hourly demand forecasting method on annual weekly and daily horizons using a linear model that takes into account the harmonics of these variations and the modulation of diurnal periodic variations by seasonal variations. The electricity demand exhibits cyclic behavior with different seasonal characteristics. Our model is based solely on sinusoidal variations and predicts hourly variations without using any climatic or econometric information. The method is applied to the Turkish power market on data for the period 2012-2014 and predicts the demand over daily and weekly horizons within a 3% error margin in the Mean Absolute Percentage Error (MAPE) norm. We also discuss the week day/weekend/holiday consumption profiles to infer the proportion of industrial and domestic electricity consumption. (C) 2017 Elsevier Ltd. All rights reserved.
Citation Count: 6
Forecasting Models For Daily Natural Gas Consumption Considering Periodic Variations And Demand Segregation
(Elsevier Ltd, 2020) Bilge, Ayşe Hümeyra; Ağca Aktunç, Esra; Bilge, Ayşe Hümeyra; Ağca Aktunç, Esra
Due to expensive infrastructure and the difficulties in storage, supply conditions of natural gas are different from those of other traditional energy sources like petroleum or coal. To overcome these challenges, supplier countries require take-or-pay agreements for requested natural gas quantities. These contracts have many pre-clauses; even if they are not met due to low/high consumption or other external factors, buyers must completely fulfill them. A similar contract is then imposed on distributors and wholesale consumers. It is, thus, important for all parties to forecast their daily, monthly, and annual natural gas demand to minimize their risk. In this paper, a model consisting of a modulated expansion in Fourier series, supplemented by deviations from comfortable temperatures as a regressor is proposed for the forecast of monthly and weekly consumption over a one-year horizon. This model is supplemented by a day-ahead feedback mechanism for the forecast of daily consumption. The method is applied to the study of natural gas consumption for major residential areas in Turkey, on a yearly, monthly, weekly, and daily basis. It is shown that residential heating dominates winter consumption and masks all other variations. On the other hand, weekend and holiday effects are visible in summer consumption and provide an estimate for residential and industrial use. The advantage of the proposed method is the capability of long term projections, reflecting causality, and providing accurate forecasts even with minimal information.
Citation Count: 42
A framework for water and carbon footprint analysis of national electricity production scenarios
(Pergamon-Elsevier Science Ltd, 2017) Kirkil, Gökhan; Küçükvar, Murat; Onat, Nuri Cihat; Kirkil, Gökhan
While carbon footprint reduction potential and energy security aspects of renewable and non-renewable resources are widely considered in energy policy their effects on water resources are mostly overlooked. This research aims to develop a framework for water and carbon footprint analysis to estimate the current and future trends of water consumption and withdrawal by electricity production sectors for national energy development plans - alongside carbon emissions from various electricity sources. With this motivation the Turkish electric power industry is selected as a case study and a decision support tool is developed to determine the water consumption withdrawal and carbon emissions from energy mixes under three different scenarios namely Business-As-Usual (BAU) Official Governmental Plan (OGP) and Renewable Energy-Focused Development Plan (REFDP). The results indicate that water is used substantially even by renewable resources such as hydroelectricity and biomass which are generally considered to be more environmental friendly than other energy sources. The average water consumption of the OGP energy mix in 2030 is estimated to be about 8.1% and 9.6% less than that of the BAU and REFDP scenarios respectively. On the other hand it is found that the water withdrawal of the energy mix in 2030 under the REFDP scenario is about 46.3% and 16.9% less than that of BAU and OGP scenarios. Carbon emissions from BAU are projected to be 24% higher than OGP and 39% higher than REFDP in 2030. Carbon emissions and water usage are strongly correlated in BAU scenario as compared with OGP and REFDP thus carbon friendly energy sources will result in fewer water consumptions and withdrawals particularly under REFDP. (C) 2017 Elsevier Ltd. All rights reserved.
Citation Count: 224
A fuzzy AHP approach to evaluating machine tool alternatives
(Springer, 2006) Ayağ, Zeki; Özdemir, Rifat Gürcan
Selecting process of a machine tool has been very important issue for companies for years because the improper selection of a machine tool might cause of many problems affecting negatively on productivity precision flexibility and company's responsive manufacturing capabilities. On the other hand selecting the best machine tool from its increasing number of existing alternatives in market are multiple-criteria decision making (MCDM) problem in the presence of many quantitative and qualitative attributes. Therefore in this paper an analytic hierarchy process (AHP) is used for machine tool selection problem due to the fact that it has been widely used in evaluating various kinds of MCDM problems in both academic researches and practices. However due to the vagueness and uncertainty on judgments of the decision-maker(s) the crisp pair wise comparison in the conventional AHP seems to insufficient and imprecise to capture the right judgments of decision-maker(s). That is why
Citation Count: 42
A fuzzy QFD approach to determine supply chain management strategies in the dairy industry
(Springer, 2013) Samanlıoğlu, Funda; Ayağ, Zeki; Büyükozkan, Gülçin
The aim of this study is to identify the crucial logistics requirements and supply chain management (SCM) strategies for the dairy industry. For product or service development quality function deployment (QFD) is a useful approach to maximize customer satisfaction. The determination of design requirements and supply chain management strategies are important issues during QFD processes for product or service design. For this reason a fuzzy QFD methodology is proposed in this study to determine these aspects and to improve customer satisfaction. Qualitative information is converted firstly into quantitative parameters and then this data is combined with other quantitative data to parameterize two multi-objective mathematical programming models. In the first model the most important logistic requirements for the company are determined based on total technical importance total cost total feasibility and total value increment objectives and in the second model based on these objectives appropriate supply chain management strategies are determined. Finally a case study from the Turkish dairy industry is given to illustrate the proposed approach.

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