بهینه سازی شبکه زنجیره تامین سبز چندسطحی-چندمحصولی فرآوری آبزیان

آلودگی های زیست محیطی، یکی از بزرگ ترین چالش های سال های اخیر جوامع بشری است که افزایش روزافزون و پیامد های مخرب آن، همچنین، افزایش نگرانی ها در این مورد، سبب پیدایش رویکرد های جدیدی تحت عنوان زنجیره تامین سبز شده است که به عنوان یک فلسفه سازمانی، می تواند خطرات زیست محیطی را کاهش دهد. در این مطالعه، یک مدل ریاضی چندهدفه در یک شبکه زنجیره تامین سبز چند سطحی و چند محصولی ارائه شده است که به کمینه سازی هزینۀ حمل و نقل، هزینۀ زیست محیطی و بیشینه سازی سطح ظرفیت زنجیره تامین می پردازد. این پژوهش از نظر هدف، کاربردی و از نظر جمع آوری داده ، پیمایشی است. در این مطالعه، پس از بررسی و مداقه مبانی نظری و پیشینه تجربی، طراحی شبکه انجام گردید. سپس، مدل ریاضی مناسب با مطالعه موردی تدوین و اعتبارسنجی آن انجام، و برای حل این مدل، از رویکرد معیار  جامع، و از نرم افزار گمز با حل کننده های سیپلکس، برای حل مدل استفاده شد. با حل مدل، مقدار متغیرهای تصمیم و دودویی محاسبه گردید. نتایج نشان داد که کارخانه اول، بیشترین ظرفیت دریافت آبزی از سه مزرعه اول، سوم و چهارم را دارد. همچنین، در زنجیره تامین آبزیان مورد مطالعه، با تاکید بر کاهش ردپای کربن، بیان می دارد که، جهت دستیابی به اهداف، کارخانه اول، به فرآوری محصول سوم، کارخانه دوم، به فرآوری هر سه نوع محصول و کارخانه سوم، به فرآوری محصول دوم، فعالیت داشته باشد.

optimization of multi-level green supply chain network - multi-product aquatic processing

in the last decade, the design of the green supply chain network has become very important due to the increase in competition in global markets to achieve success, which requires the simultaneous commitment and cooperation of suppliers, manufacturers and distributors in the form of a network. one of the generalizable fields of the green supply chain network is the aquatic processing industry as one of the most important food industries that has paid less attention to optimize its supply chain in order to provide environmental benefits. in recent decades, the demand for food has increased more than the capacity to provide resources for it. hence, the traditional food supply chain can no longer effectively manage demand. the increase in world population, globalization, global warming, drought and groundwater crisis in recent years have led to the loss of natural resources needed for animal husbandry and the reduction of marine reserves in iran as well as in other middle eastern countries. the expansion of aquaculture farms has not only contributed to the development of sustainable food in the country, but has also been very effective in preserving endangered species. the aquaculture industry has grown significantly in recent decades. in this industry, green supply chain network design seems to be critical for aquatic processing.methodologythis study is a descriptive research and applied one in terms of purpose. in this research, after examining the theoretical foundations and experimental background, the network design was proposed. the aquatic supply network was designed in three levels, for four farms, three factories, and two customers. the first level includes aquaculture farms. the second level consists of models of aquatic processing factories. the third level includes customer networks. of course, other levels of the aquaculture supply chain, i.e. retailers, can also be considered in network design. then the appropriate mathematical model was formulated and validated with a case study. lp-metric method was used to solve this model. the gams software was used in this study.findingsin this research, the network of green aquatic management has been designed to achieve the goals of minimizing costs and carbon dioxide emissions and maximizing the capacity of units at three levels for four farms, three factories, and two customers. in this research, after drawing the network of the problem and explaining the mathematical model, it was solved using the comprehensive criterion method with p equal to 1, 2, and 3. the value of the objective function was calculated with p equal to 0.09. by increasing the value of p, it became clear that there is no distance between the values of the objective functions and the ideal values. then, the value of decision and binary variables was calculated. the first factory has the highest aquatic receiving capacity from the second, third and fourth farms.discussion and conclusionin order to achieve the goals with an emphasis on reducing the carbon footprint, the first factory should process the third product, the second factory should process all three types of products, and the third factory should process the second product. in this research, certainty is considered for the parameters. if the surrounding environment is very dynamic, this turbulence can increase the uncertainty of model parameters. therefore, it is suggested to solve the research model assuming uncertainty in the parameters in other researches. in this research, the same weight has been considered for three purposes.in this study, it is assumed that the transportation cost between nodes depends only on the distance. it is important to note that the cost of transportation between two points can be affected by various factors. therefore, it is suggested to pay attention to these factors in other researches. using the research model can minimize the total costs in the aquaculture network and maximize the capacity of using the components of the entire chain, bringing the environmental destruction to the lowest level. therefore, it is suggested to use this model. one of the factors affecting the production and emission of carbon is the number of car trips. in other words, the lower the number of trips (carrying times), the lower the emissions. it is suggested managers to use a means of transportation with a higher capacity. timely servicing of goods transport vehicles can also be effective in carbon emissions. it is recommended to periodically repair the car. in the chain under study, most of the cars were worn out and without fuel consumption reduction technology. it is suggested to replace the old vehicles carrying goods with modern and high-tech vehicles. it is recommended to use gas-fueled vehicles for transporting goods.