جستجوی مقالات مرتبط با کلیدواژه "mixed integer programming" در نشریات گروه "فنی و مهندسی"

This paper proposes a bi-objective model for a green closed-loop supply chain network design. Four levels for forward and five levels for reverse flow were considered, including plants, distribution centers, online retailers, traditional retailers and customers for forward flow and customers, collecting centers, disposal centers, repair centers and plants for the reverse flow. The objectives are minimizing the GHG emission and maximizing profit by considering defective products and a second market for these products. Also, online retailers were considered alongside with traditional ones, since the Covid-19 pandemic has led to increase in the amount of online shopping. GAMS software and the Lpmetric technique were used to solve the model in the small and medium sizes. However, for the large size, we used Grasshopper Optimization Algorithm (GOA) as a meta-heuristic approach since solving the large size problem with GAMS is a complicated and time-consuming process. We provided Numerical and computational results to prove the efficiency and feasibility of the presented model. Finally, the managerial insights and future works were provided.

The ceramic and tile industry is one of the traditional Iranian jobs used in every historical period of different forms. Iran is one of the five largest producers of tiles and ceramics, which have been able to become the biggest exporter of these products in Western Asia by having a huge capacity in the industry. In recent years, ceramics and tiles exports have become one of the country's most important foreign trade. Therefore, to achieve a larger part of the export share, the competitive environment has dominated the industry. On the other hand, supply chain management is considered more and more attention due to the increasing globalization of industries and international competition. Many companies prefer to supply and manage their procurement, production and distribution sectors separately in several countries. Therefore, in dealing with global competitiveness, how to design a supply chain network with minimum cost and with emphasis on financial considerations, insurance and customs, has become an important issue for multinational companies. In this paper, using mixed integer programming method, a four level global positioning model is proposed considering the limitation of water consumption in the production line using GAMS software. The proposed model was used in one of the ceramic tile manufacturing industries in Yazd province to validate the model and investigate the effect of important parameters on strategic location decisions, which led to the location of two domestic warehouses and three foreign distribution centers in neighboring countries.

The resilient supply chain considers many capabilities for companies to overcome financial crises and to supply and distribute products. In this study, we address the allocation of inventory distribution for a distribution network, including a factory, a number of potential locations for distribution centers and a number of retailers. Customers demand is assumed to be certain and deterministic for all periods but time varying in the limited planning horizon. The proposed model in this research is a linear complex integer programming model with two-objective functions. The first objective function minimizes the total costs of the entire distribution system in the planning horizon, and the second objective function seeks to minimize the difference between the maximum and minimum distances traveled by vehicles over the planning horizon. Therefore, the model tries to satisfy the demand and at the same time reduce costs using the best route transportation option configuration and transportation option. The routing problem is developed, and as the problem is a NP-hard problem, a meta-heuristic method is used to solve it. In this model, the demand volume for each customer in a period of the network, vehicle capacity, factory capacity, constant transportation cost, variable transportation cost, etc., are considered as factors affecting the model. The results show that the model proposed in the network can be used as a lever to improve the performance of the financial economic supply network through saving in routes.

Recently, following the raise in expense pressures led to lower economic growth, an increasing number of manufacturers have begun to investigate eventuality of handling returned product in a more cost-effective and proper procedure. Significance of Reverse Logistics (RL) is becoming greater due to various governmental, societal, and environmental reasons. Number of papers present in the literature on RLs is a well index of its importance. In some industries, appropriately collected returned products could be used as raw material for another product, increasing Supply Chain (SC) profits and reducing the waste. Since, perishable goods have a limited shelf -life, they can be reusable if they are collected before they reach a critical time. Accordingly, in the present study, a Mixed Integer Linear Programming (MILP) model was introduced for a network of closed-loop SC with recycling of returned perishable goods, involving suppliers, producers, retailers, together with collection and disposal centers, in a multi-product, multi-period, and multi-level basis. To do this, a case study was performed on milk and yogurt products of a company in dairy industry. The model was solved and analyzed using GAMS software. Results obtained from assessment of the model indicated that, timely collection of perishable goods and their use in production of new products reduces total costs of perishable SC network.

In this paper, we present an integrated model to find the optimum size of blast block that uses (i) a multi-criteria decision-making method to specify the applicable size of the mineable block; (ii) a linear programming method for the selection of the blasted areas to be excavated and in deciding the quantity of ores and wastes to be mined from each one of the selected blocks. These two methods use improved estimates of the orebody characteristics utilizing the blast hole data in addition to the usual borehole statistics to improve the prediction accuracy of the block level ore body characteristics. This work aims to make a mathematical model to figure out the ideal width and length of the blast block in order to curtail drilling and blasting expenses in open-pit mines. As a consequence, the effective blast block size is heeded so as to decrease the expenses of drilling and blasting. Furthermore, a complete set of actual principles is presented to specify the applicable size of the mineable block by means of the multi-criteria decision-making method of fuzzy logic. The aforementioned model is practiced to forecast the block size necessary for the purpose of production planning. Next, a mixed integer programming model is developed to blast planning in order to select the optimal size of the blast block by considering the mineable block. The proposed model is applied in the Chadormalu iron ore mine and the rationality of the model is demonstrated by the outcomes of dissimilar circumstances.

Due to the ever-growing load, especially peak load, the increase in the capacity of plants is inevitable for the response to this growth. Peak load causes increases in customer costs and vast investments in generating and transmission parts. Therefore, restructuring in the electrical industry, competition in the electrical market and Demand Response Programs (DRPs) are of special importance in power systems. In DRPs, customers in certain periods, such as peak or times when the price is high, decrease self-consumption. It means profit for costumers and prevention of expensive production in peak time for a genera-tion source. Moreover, to decrease the operation cost of network and ever-growing technology significantly, the power sys-tems operators have employed new sources of energy production as well as thermal units, and it has led to the emergence of Electric Vehicles (EVs) technology as a new source of energy production. This paper studies the simultaneous presence of DRPs and EVs to minimize the total operation cost of a network from one hand and from the other to improve the level of system reserve in Unit Commitment (UC) problem with considering the security constraint. Here, the proposed framework is structured as a Mixed Integer Programming (MIP) and solved using CPLEX solver.