Increased concern about global warming in today's world has led to the legislation of regulations that seek to gradually reduce the amount of greenhouse gases emitted by industrial sectors and along their supply chains. This study focuses on the amount of carbon emitted in a two-echelon supply chain in which one supplier delivers a single product to a group of retailers and attempts are made to integrate and coordinate its different members. A mixed integer programming model is thus developed in which the problems of timing and the amount of replenishment for each retailer, the types of vehicles used for transportation as well as the amount of products that must be carried by each type of vehicle are addressed with the aim of reducing the overall cost of the supply chain and its carbon footprints. The objective of this research is to minimize the costs of transportation and those engendered by material handling and inventory holding activities as well as to reduce carbon emissions throughout the supply chain. In order to carry out various scenario analyses, some numerical instances are provided and solved. According to the results obtained, the supplier will opt for lower carbon vehicle types if replenishment timing, distances between members of the supply chain, the rate of carbon tax or the amount of retailers increases.
This study is an applied, analytic-descriptive research in terms of nature. It is thus an analysis in which a sample has been applied for data collection and it is descriptive since its variables are assessed and reported as they are in reality. This study seeks to identify effective risks existing in construction industry specifically in the national macro projects such as oil industry projects through utilizing Project Management Body of Knowledge (PMBOK) model and to estimate the relative impact of each risk on the projects. It aims at prioritizing the effective risk factors on the construction projects (a case study of National Iranian Oil Company). Thus NIOC construction projects, consulting engineers companies and contractor companies in construction projects of oil industry have been selected as the statistical universe to identify and prioritize the risks. Due to the focus of oil industry construction projects on South Pars Special Economic Zone, under planning, implementation or completion phases and with regard to the phases' expansion in terms of number and volume of activities and also strategic features and confidentiality of information, three phases out of 28 ones have been case-studied. It is generally concluded in this study that with respect to the country significant strategic, geopolitical, geographical, economic and military position in the world, it is a matter of great magnitude to regard the risks identification and management as one of the important areas in the project management and to consider it as a national and comprehensive plan when designing and ratifying industrial projects of the country.
This paper attempts to develop four types of acceptance sampling plans under the objectives of minimizing the total loss to the producer and consumer and maximizing the rate of approaching to the ideal operating characteristic (OC) curve when the quality characteristic follows a normal distribution and has lower specification limit. To provide the desired protection for both the producer and the consumer, two constraints are considered that balance both producer and consumer risks by using two specified points on OC curve. The first objective function of this model is constructed based on the total expected loss by incorporating the one-sided minimum specification Taguchi loss function, and the second one is constructed based on conformity to the ideal OC curve by using minimum angle method. Also, the optimal solution of the proposed plans is determined for 10 different scenarios of process parameters. Furthermore, the optimal solution of these plans is determined when only one of the objective functions is considered.
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