maghsoud Amiri; mohsen shafiei nikabadi; Armin Jabbarzadeh
Abstract
In recent years, the complexity of the environment, the intense competition of organizations, the pressure of governments on producers to manage waste products, environmental pressures and most importantly, the benefits of recycling products have added to the importance of designing a closed loop supply ...
Read More
In recent years, the complexity of the environment, the intense competition of organizations, the pressure of governments on producers to manage waste products, environmental pressures and most importantly, the benefits of recycling products have added to the importance of designing a closed loop supply chain network. Also, the existence of inherent uncertainties in the input parameters is another important factor that the lack of attention them can affect the strategic, tactical and operational decisions of organizations. Given these reasons, this research aims to design a multi-product and multi period closed loop supply chain network model in uncertainty conditions. To this aim, first a mixed-integer linear programming model is proposed to minimize supply chain costs. Then, for coping with hybrid uncertain parameters effectively, randomness and epistemic uncertainty, a novel robust stochastic-possibilistic programming (RSPP) approach is proposed. Furthermore, several varieties of RSPP models are developed and their differences, weaknesses, strengths and the most suitable conditions for being used are discussed. Finally, usefulness and applicability of the RSPP model are tested via the real case study in an edible oil industry.
hadis drikvand; seyyed mohammad hajimolana
Abstract
Environmental concerns have spurred an interest in studying green supply chain. Nowadays, governmental and non-governmental organizations consider environmental management as a strategic requirement having numerous benefits. Therefore, they effort to increase customers' satisfactory and market share ...
Read More
Environmental concerns have spurred an interest in studying green supply chain. Nowadays, governmental and non-governmental organizations consider environmental management as a strategic requirement having numerous benefits. Therefore, they effort to increase customers' satisfactory and market share considering external factors like environmental consequences in addition to internal factors. In this paper, a bi-objective mixed integer programming model is developed to identify the optimal location for manufacturers and disassembly sites in a green supply chain network design. This paper addresses the role of the reliability of facilities and vehicles to ensure effective stream among supply chain network, the objective functions are defined as total cost minimization, and total co2 emissions minimization. Besides, uncertainties on the network design are investigated through two-stage stochastic programming. with respect to the fact that the model is non-linear and bi-objective, at first, an approach is presented to linearize it and then the proposed bi-objective mathematical model is solved as a single-objective one by compromise programming method. The effectiveness of the proposed model is demonstrated by using of a numerical example derived from a real case.
