Browsing by Author "Ozfirat, PM"

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    A CONSTRAINT PROGRAMMING HEURISTIC FOR A HETEROGENEOUS VEHICLE ROUTING PROBLEM WITH SPLIT DELIVERIES
    Ozfirat, PM; Ozkarahan, I
    This article considers fresh goods distribution of a retail chain store in Turkey. The problem is formulated as a vehicle routing problem with a heterogeneous fleet for which no exact algorithm has ever been designed to solve it. A fast and effective algorithm based on constraint programming is proposed for the solution. The procedure is tested on some of the benchmark problems in literature. The real-life case is first solved assuming that delivery of a customer cannot be split between vehicles. Then it is resolved considering split deliveries. Solutions of both strategies are compared with the current performance of the firm to determine a distribution strategy. Results indicate considerable improvement in the performance of the firm.
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    Setting order promising times in a supply chain network using hybrid simulation-analytical approach: An industrial case study
    Tunali, S; Ozfirat, PM; Ay, G
    Supply chain management (SCM) involves the management of material and information flow among the members of chain such as vendors, manufacturing plants and distribution centers. The main processes in supply chain are production planning, control, distribution and logistics. Effective management of all these processes provides the manufacturing companies great advantages in time based competition. In order to gain a competitive edge, firms must be able to deliver their products fast and on-time. This can be managed by better production planning, scheduling and due-date setting. This paper suggests a hybrid approach for setting realistic order due dates for a produce-to-order manufacturing company operating within a supply chain environment. The proposed hybrid approach combines mathematical and simulation modeling to bring together the advantages of both approaches. (C) 2011 Elsevier B. V. All rights reserved.
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    Risk Management for Surface Plants in Mines using Risk Matrix and BowTie Analysis
    Ozfirat, MK; Ozfirat, PM; Yetkin, ME
    Surface plants in mines are important parts of a mine operation. There exist offices, common areas, repair and maintenance shops, compressed air facilities, hydraulic facilities, areas where mine machinery and parts are stacked, transportation cranes and mine stock areas in surface plants. Therefore, while the mining operations are continuing, it is necessary to control all the work in the surface plants in terms of work safety and health. In this study, the risk matrix method is used to identify and prioritize the risks of surface plants in a mine. Then, the highest priority risk, which is found to be Stock area and work environment, is considered using bowtie analysis. Four threats are determined for Stock area and work environment risk. These are improper ore or coal stock area, insufficient lighting in night works, lack of maintenance of field crane and dusty work environment. These threats are also modelled using bowtie analysis. As a result of this study, these threats, corresponding barriers and consequences can be managed by safety and operational engineers.
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    Truck Selection with the Fuzzy-WSM Method in Transportation Systems of Open Pit Mines
    Malli, T; Ozfirat, PM; Yetkin, ME; Ozfirat, MK
    Open pit mines gain width and become more complicated as they are deeper today, and it is inevitable to carry the produced material with a truck transportation system. Therefore, in large-scale businesses, truck selection has great importance for the transportation costs to be sustainable. This study investigates the main factors and corresponding criteria influential in selection of trucks, which are the most frequent used means of transportation in open pit mines. Analytic hierarchy process and fuzzy weighted sum model are employed to solve the selection problem. Six different truck types and 20 selection criteria are considered. As a result of technical analysis, most suitable trucks are found.
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    Integration of fuzzy analytic hierarchy process and multi-objective fuzzy goal programming for selection problems: An application on roadheader selection
    Ozfirat, PM; Ozfirat, MK; Malli, T; Kahraman, B
    In this study a general methodology employing fuzzy analytic hierarchy process and fuzzy goal programming is developed for selection problems. The proposed methodology has two main sub-phases. In the first phase, fuzzy triangular numbers are used in order to represent the comparisons among decision criteria. Then lower and upper bounds as well as mid-values of priorities belonging to each decision criteria are computed. In the second phase these values and fuzzy triangular numbers are entered into the goal programming model and the model is solved to give the final priorities of decision criteria. Then the weighted sum of ratings for each selection alternative are found where the weights are final priorities from goal programming model. The proposed methodology is presented on a real life roadheader selection problem from mining industry. The results revealed that the methodology is easily applicable and provides satisfactory results.
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    A FUZZY APPROACH TO SELECTING ROOF SUPPORTS IN LONGWALL MINING
    Yetkin, ME; Simsir, F; Ozfirat, MK; Ozfirat, PM; Yenice, H
    As a decision-making problem, selecting proper machines and equipment plays a key role for mining sites and companies. Many factors affect this decision, and values belonging to these factors can be expressed numerically and/or non-numerically. In order to make the most appropriate decision, engineers must carry out an evaluation process that comprises all criteria that might affect decision-making. To achieve this, multi-criteria decision-making tools are used. As a result of technological developments, coal outputs in longwall mining have risen tremendously over the last decades, and longwall mechanisation has become unavoidable. The significance of powered roof supports in particular increases day-by-day, since the rate of roof support has to be in accordance with the rate of face advance in longwalls. In this study, an integrated fuzzy analytic hierarchy process and fuzzy goal programming model is used to select the most suitable powered roof supports. The procedure is applied to a real-life underground coal mine that is operated using the longwall method. Seven alternative powered roof supports are compared with each other, taking a total of 24 decision criteria under four main topics into account. In conclusion, the most suitable roof supports for the mine under study are determined and recommended to the decision-makers of the system.
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    A FUZZY ANALYTIC HIERARCHY PROCESS METHODOLOGY FOR THE SUPPLIER SELECTION PROBLEM
    Ozfirat, PM; Tuna, G; Tuncel, G
    Purchasing activities of a company form a very important part in the operation of the company. The quality of production and services mainly rely on the performance of the suppliers. In addition, a large amount of the product's total cost belongs to the purchasing cost of its materials. Therefore, selecting the most suitable suppliers is very important for the firm. Unfortunately, most of the time, suppliers cannot provide the highest quality parts on-time at the lowest costs in the market. In other words, quality, delivery and cost objectives conflict with each other. In this study a fuzzy analytic hierarchy process approach is employed for the supplier selection problem of a textile company. First the selection criteria according to company's objectives are determined. Then the pair-wise comparisons are made on a fuzzy basis. Similarly, in the next step, the six alternative suppliers are compared by fuzzy means. Finally, the two suppliers which achieved the highest performance are advised to the company.
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    A FUZZY EVENT TREE METHODOLOGY MODIFIED TO SELECT AND EVALUATE SUPPLIERS
    Ozfirat, PM
    The supplier selection problem becomes more urgent as competition in the market increases. Quality, cost, and the timely delivery of a product mostly depends on the manufacturer's suppliers and the materials supplied. Therefore manufacturers are very elaborate in selecting their suppliers and work hard to develop supplier selection strategies. In this study, event tree analysis (ETA) is used to solve a manufacturing firm's supplier selection problem. ETA is a method that is traditionally used for risk analysis problems, combining the probabilities of risk occurrences subject to the necessary precautions. In this study, this structure is used to select and evaluate suppliers. An event tree is developed to analyse each possible supplier, with branching being used according to the supplier selection criteria. The probability of each branch is set as the performance value of the supplier according to the selection criteria. Finally, the supplier is evaluated by combining all performance values on an event tree basis. Fuzzy logic is also incorporated into the event tree methodology to decrease human error and the effect of uncertainty. Fuzzy triangular numbers are used to denote the performance values of suppliers, and fuzzy ranking is used to distinguish the suppliers into classes. The proposed methodology is applied to nine possible suppliers of a specific material. The results reveal that two of the suppliers dominate all the others in the fuzzy ranking.
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    Comparison of artificial neural networks and regression analysis for airway passenger estimation
    Ari, D; Ozfirat, PM
    With the increasing demand in operations, time is getting more important. In order to use time and energy more effectively, it is becoming more important for airline companies and airport managements to make strategic plans for the future. To make beneficial and correct strategic plans for airways, one of the factors that is needed to be considered is future passenger numbers. With more accurate passenger number forecasts, airport managements can act more efficiently and reduce time, energy consumption and hence would be able to reduce costs. In this study, airway passenger number estimation is handled. Three metropolitan cities' airport passenger numbers are considered. Artificial neural networks and regression analysis are carried out to estimate passenger number. In addition, data are handled in two different ways. Firstly, ANN and regression analysis are applied using original data series. In the second step, seasonal decomposition is applied on the data series and both approaches are repeated for deseasonal series. In Artificial Neural Networks approach, an experimental design is developed considering training algorithms, number of input nodes and number of nodes in the hidden layer which make up 960 design points. In the results of these experiments, performance of ANN approach is tested for three input factors and high-performance design points are identified. Furthermore, for benchmarking purposes, regression analysis is carried out. Linear, logarithmic, power, exponential, and polynomial models are developed. Finally, results of ANN and regression approaches are compared in terms of mean absolute percent error, and it is found that ANN overperformed compared to regression analysis.
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    An integer programming approach for the three-dimensional cutting planning problem of marble processing industry
    Ozfirat, PM
    The three-dimensional cutting problem is one of the major problems faced in the marble factories. Huge marble blocks coming from marble quarries are first cut into planes according to their depths. Then these planes are sized according to the length and width of the demanded products. In this study, the cutting problem of a marble processing factory is handled. Two different integer programming (IP) approaches are developed. In the first one, an IP model is built for each of the two cutting problems, which are cutting marble blocks into planes and sizing these planes. In the second approach, these two IP models are integrated together to handle the two different cutting operations together. The objective of both models is to minimize total spoilage of marble while finding the cutting designs of the marble blocks and marble planes. A number of real life problems are solved using both approaches. Computational results are compared statistically. Results showed that both approaches decrease the wasted amount of marble compared to the industry's average.