In this research, a tri-objective mathematical model is proposed for the Transportation-Location-Routing problem. The model considers a three-echelon supply chain and aims to minimize total costs, maximize the minimum reliability of the traveled routes and establish a well-balanced set of routes. In order to solve the proposed model, four metaheuristic algorithms, including Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Water Cycle Algorithm (MOWCA), Multi-objective Particle Swarm Optimization (MOPSO) and Non-Dominated Sorting Genetic Algorithm- II (NSGA-II) are developed. The performance of the algorithms is evaluated by solving various test problems in small, medium, and large scale. Four performance measures, including Diversity, Hypervolume, Number of Non-dominated Solutions, and CPU-Time, are considered to evaluate the effectiveness of the algorithms. In the end, the superior algorithm is determined by Technique for Order of Preference by Similarity to Ideal Solution method. تفاصيل المقالة

In this article, a sustainable network of distribution of agricultural items with suppliers, distribution centers, and retailers is considered. The main purpose of presenting the mathematical model in this article is to determine the optimal number and location of suppliers, assigning suppliers to distribution centers and optimal routing for the distribution of agricultural items to retailers in a predefined time window. Also, determining the optimal amount of inventory and the reorder point in retailers and distribution centers is another problem decision. To model the problem, some parameters of the model were considered non-deterministic and were controlled by the probabilistic fuzzy method. The results of solving numerical examples in different sizes showed that with the increase of the total costs of the distribution network of agricultural items, the amount of greenhouse gas emissions decreases, and the employment rate increases. Also, with the increase of the uncertainty rate, due to the increase of the real demand and the change in the optimal amount of production, distribution, storage and reorder point, the values of all the objective functions also increase. It was also observed by solving different numerical examples with NSGA II and MOGWO algorithms, these algorithms have been able to solve the problem in a much shorter period than the epsilon constraint method, and comparison indicators such as NPF, MSI, SM, and computing time show These algorithms have a high efficiency in solving numerical examples of the problem of the distribution network of agricultural items. تفاصيل المقالة

Integrated and coordinated planning of the main functions of the supply chain (procurement, production and distribution) often leads to economic efficiency and, as a result, more profit for the entire supply chain. On the other hand, the financial flow and the flow of goods and information are crucial and influential flows in any supply chain. In this paper, the main contribution is to integrated planning of procurement, production and distribution for a multi-product supply chain in order to maximize the producer's profit and also minimize the deviations of the producer's financial indicators by considering both the physical and financial flow. In this regard, the studded supply chain includes several suppliers, one producer and several customers. One of the prominent features of the proposed model is the use of mathematical programming to model the financial flow and achieve the producer's financial goals. Since the presented model is a bi-objective one, two fuzzy multi-objective interactive methods, Selim and Ozkarahan (SO) and Torabi and Hassini (TH) can adjust the degree of satisfaction of the objective functions have been applied. Next, the model is optimized using the goal programming method. Finally, the numerical results in optimizing the proposed fuzzy model show the proposed model's efficiency and the high quality of performance and applicability of the proposed model. The core achievement in the numerical results is that the total value of the distribution in the two models is equal. However, the SO method obtains more unbalanced solutions when the decision maker pays more attention to the first objective function. تفاصيل المقالة

در سیستم های تولیدی و صنعتی، برنامه ریزی ادغامی تولید و عملیات و تعمیرات از اهمیت بسیار زیادی برخوردار است. از این رو در این پژوهش یک برنامه ریزی ادغامی چندهدفه با قابلیت بهینه سازی برای زمان‌بندی تولید و نگهداری و تعمیرات با ملحوظ دانستن محدودیت دسترسی به منابع تولیدی در شرایط عدم قطعیت ارائه شده است. برای این منظور، یک مدل ریاضی برنامه ریزی مختلط عدد صحیح در راستای برنامه ریزی تولید و نگهداری و تعمیرات در شرکت مارون مدل سازی گردید. بر طبق نتایج حاصل شده، ماکزیمم سود حاصل شده پس از کسر هزینه‌ها برابر با 12690 میلیون دلار، کمترین ریسک ناشی از تولید محصول برابر با 3462 و کمترین مدت زمان اجرای نگهداری و تعمیرات برابر با 14172 ساعت محاسبه شده است. سرانجام، نتایج ارزیابی مدل سازی انجام شده نشان داد که استقرار نتایج حاصل از حل دقیق و فراابتکاری ارائه شده در این مقاله بیش از 7 درصد در تولیدات شرکت بهبود ایجاد می‌کند. تفاصيل المقالة