رویکرد مبتنی بر فرایند شبکه تحلیلی فازی برای انتخاب حالت حمل و نقل بین ترکیه و آلمان : مطالعه موردی
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|6084||2008||14 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 9068 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
|شرح||تعرفه ترجمه||زمان تحویل||جمع هزینه|
|ترجمه تخصصی - سرعت عادی||هر کلمه 90 تومان||13 روز بعد از پرداخت||816,120 تومان|
|ترجمه تخصصی - سرعت فوری||هر کلمه 180 تومان||7 روز بعد از پرداخت||1,632,240 تومان|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Information Sciences, Volume 178, Issue 15, 1 August 2008, Pages 3133–3146
A case study examining the different modes for transportation of freight by a Turkish logistics-service provider company is presented herein. A number of conflicting qualitative and quantitative criteria exist for evaluating alternative modes of transport. Qualitative criteria are often accompanied by ambiguity and vagueness. To cope with ambiguity and vagueness problem, the fuzzy analytic network process (ANP) method has been used. A large number of detailed criteria that interact with each other have been evaluated and synthesized to obtain the most suitable transportation mode. This evaluation has been carried out by a group of decision makers coming from different management levels and functional areas in the sector of logistics and from the service company with intent to provide a more accurate and mutually acceptable solution. Furthermore, the model used here has been validated by comparing the results obtained with the current preferences of the company.
Increasing the volume of trade relative to the globalization of world trade promotes lower costs for logistics and increased customer satisfaction that maintain long-term strategical competitiveness. The prevalent market economy places significant importance on having the right item at the right time in inventory in addition to providing the item to the customer within the desired timeframe. This requires the simultaneous consideration of both the inventory and the transportation functions of the supply chain. Transportation, one of the main subjects in logistics, is considered a process that benefits from all the modes of transportation. Transportation decisions include transportation-mode selection, shipment size, vehicle routing, and scheduling; all of these are directly related to the location of warehouses, customers, and factories. The relocation of warehouses and factories causes considerable changes in the transportation decisions at the strategic, tactical, and operational levels. At the strategic level, selection of the appropriate transportation mode is the most important concept in shipment planning. The four main modes of transportation for freight and passenger traffic, which have their own advantages and disadvantages, are rail, road, water, and air. Each of these modes has different characteristics, and any of them can be considered the best under different circumstances, depending on the location, distance, type of freight, and value of freight, among other things. In the selection of a particular mode, all the advantages and disadvantages related to the concerned mode of transport have to be considered. Under certain conditions, the choice of a transportation mode may seem obvious, but a comparison that depends on a variety of criteria may be nevertheless required. The main criteria for transportation are the type and volume of freight and the distance to be covered. Other criteria may include speed, availability, reliability, capacity, security, and frequency of delivery. Each type of criterion has its own character; in other words, a number of possibly conflicting criteria exists for evaluating different transportation modes. Identifying these qualitative and quantitative evaluation criteria, defining their inter-related effects, assessing their importance, and choosing a particular transportation mode requires a well designed multiple-criteria decision-making (MCDM) based evaluation. Many researchers have studied the determination of suitable transportation modes using different methods , , , , , ,  and . Due to the mutual dependencies and feedback effects of the criteria, the analytic network process (ANP) can be used to systematically evaluate the most suitable transportation modes. The ANP is a multiattribute approach to decision-making that facilitates the transformation of qualitative values into quantitative values, enabling their analysis. Many problems that require a systematic decision cannot be hierarchical because of the dependencies of the criteria (inner/outer) and the influences between and within clusters (criteria, alternatives). The ANP is a relatively simple and systematic approach that can be used by decision makers. Essentially, it is a more general form of the analytical hierarchy process (AHP), first introduced by Saaty . The AHP is a special case of the ANP and contains neither feedback between nor loops within the criteria clusters representing inner dependence. Furthermore the ANP, tolerates complex interrelationships between the criteria and decision levels, but the decision-making structure in the AHP model uses unidirectional hierarchical relationships among the decision levels ,  and . The evaluation criteria for transportation-mode selection are generally not independent of each other but are often interactive. Due to the different levels of criteria interacting with each other simultaneously in the mode-selection process, an invalid and unexpected result can be obtained in the face of this complexity. Hence, the traditional AHP method that neglects the mutual effect of different conflicting levels in this kind of selection process is not suitable for the problem under consideration. To deal with this dynamic problem and to handle interdependence among the criteria at different levels within the model, the ANP approach is used. Furthermore, a large number of criteria interacting with each other, and located in different clusters, are considered in a real-world case study. Complex decision-making problems, such as transportation-mode selection, which consist of a large number of interdependent criteria, are effectively solved using the ANP whereas the AHP can be only used for hierarchical decision structures. Many precision-based methods for transportation-mode selection have been investigated, and most of them have been developed on the basis of accurate measurements and crisp evaluation. However, most of the selection parameters cannot be given precisely, and the required data for the suitability of the alternative modes with respect to various subjective criteria and the weights of the criteria are usually expressed in linguistic terms by decision makers. This makes fuzzy logic a more natural approach to this kind of problem. Fuzzy logic has been commonly used in different studies associated with transportation decisions, such as shipment size  and , vehicle routing  and , and scheduling  and . Because of certain usage limitations, such as nonnormalized fuzzy ratings and fuzzy weights, fuzzy-logic based MCDM methods may be efficiently applied to the problem of transportation-mode selection. Moreover, the fuzzy-ANP (FANP) method can be used to cope with uncertain human judgments . Several researchers have attempted to use the FANP method for different problems. Although ANP has also been applied to a large variety of decision-making processes for different applications, FANP has received much less attention in research , , ,  and . There are a few publications using the ANP method for solving transportation problems; however, there is no evidence that the FANP method has been specifically applied to transportation-mode selection. A fuzzy extension of ANP with fuzzy pair-wise comparisons and a feedback between the criteria has been proposed by Ramik . The remainder of this paper is organized as follows: Section 2 describes the contents of the ANP process; triangular fuzzy numbers are briefly reviewed in Section 3; Section 4 describes the basics of the FANP; in Section 5, a FANP-based transportation-mode selection model has been proposed, an application of the model to a logistics-service provider company is presented, and comments on the results obtained are provided. The paper is concluded in Section 6.
نتیجه گیری انگلیسی
Combining many detailed criteria in an evaluation study and synthesizing them to obtain a transportation-mode selection is the main contribution of this study. Moreover, a decision-making group from different management levels and from different functional areas related to transportation activities are brought together to evaluate these criteria and alternative modes. The criteria are linked with each other and affect the selection of the best transportation mode alternatives. Although ANP has features relative to these feedback relations, it is not a sufficient method. Another contribution of this study is to provide facilities for decision makers in the evaluation phase of the questionnaire. Instead of giving precise numbers as the comparison values, studying the situation using fuzzy numbers, could provide accuracy in many real-world decisions. The FANP model encompasses and solves the ambiguity and imprecision of the pair-wise comparison process substantially. It succeeds in deriving priorities from both consistent and inconsistent judgments. Using this fuzzified structure also gives flexibility to the experts and represents probable changes in the nature of the comparisons. As a result, using FANP for the transportation-mode selection problem is another major contribution of this work. The FANP model was applied to a large-sized real-life problem related to the transportation project between Turkey and Germany. Applying the technique to the company, which already has a chosen alternative mode, gives the opportunity of comparing the results of the FANP method with the current preferences of the company. Additionally, a validation of the model has been achieved because the FANP results obtained are similar with the current preferences. In addition, some scenarios are derived after considering the results and presented to the decision-making group for evaluation. In future research, the transportation-mode weights obtained in this study can be used in different mathematical transportation models. As mentioned in the introduction, there are different studies that attempt to solve transport optimization problems, which include the mode selection phase. Generally, the main problem of these models can be related to assignment, network construction, routing etc., and selecting the convenient transportation mode in some phases of the network is considered as a subsidiary objective. However, only transportation-mode selection has been focused on in this study in a detailed manner. In further studies, assigning the transportation-mode weights obtained by the FANP technique to include many evaluation factors, in addition to the main criteria such as cost or time, will be attempted.