جستجوی مقالات مرتبط با کلیدواژه « زنجیره تامین گاز طبیعی » در نشریات گروه « مدیریت »

Recently, governmental legislations, limitation of natural resources and adverse effects of End-of-Life products on ecological system have spurred researchers to design closed-loop supply chains. Natural gas has been used globally as a transitional fuel for supporting a green-energy-supply strategy, which has been questioned for the intermittence and lack of reliability of renewables. Natural gas has a complex and large supply chain including fields, processing plants, transmission pipelines, and distribution centers, etc. This article develops a theoretical conceptualization of supply chain uncertainty, based on the foundation provided by contingency theory. However, a qualitative analysis of the uncertainties and their sources is missing. Therefore, in this paper the authors propose an empirical approach to the identification of uncertainty occurring in the closed‐loop supply chain of Natural Gas Supply Chain (uncertainty in supply, process, demand, control, and environmental uncertainty). The investigation methodology consists of a content analysis of press media documents related to natural gas industry. Consequently, the evidences of uncertainty found are classified in a spectrum between statistical uncertainty and total ignorance (levels of uncertainty). In order to remain competitive in the market, firms are forced to expand their product offerings and offer high levels of customization, bringing about high uncertainty in their supply chain.

In today’s competitive world, uncertainty is an integral part of all optimization problems. One of the cases where uncertainty has the greatest impact on optimization issues is SCN design. In most of the conducted studies, parameters such as demand, transportation cost and capacity of tehsils have been published in an uncertain manner. In this type of problem, various methods have been used to control these uncertainty parameters, which can be referred to as fuzzy programming, robust optimization, two-stage stochastic programming, multi-stage stochastic programming, multi-stage fuzzy stochastic programming, fuzzy robust optimization. Each of the mentioned methods has limitations in terms of its implementation. in the fuzzy programming method, there is no deviation from the data collected by experts’ opinions. In probabilistic methods, it is very difficult to determine the exact type of distribution function. Therefore, many researchers have investigated the strengths and weaknesses of each method in their studies. Therefore, in this paper we try to review the strength and weakness of these methods to apply the best approaches for different situations. In this paper, a real-world case study of a natural gas supply chain is investigated. By using concepts related to natural gas industry and the relations among the components of transmission and distribution network, a Five-level supply chain has been introduced and presented schematically.