Solving multi-objective supplier selection and quota allocation problem under disruption using a scenario-based approach

Nowadays, experts believe there are abundant sources of risks in a supply chain. An important group of risks against a supply chain is the disruption risks group, which disturbs the flow of material in the chain and may lead to inefficiency in providing the final product in the supply chain. The aim of this article is to investigate the control of costs of disruption in a supply chain by considering the possibility of disruption. In fact, this research focuses on determining the best combination of suppliers and quota allocation with regards to disruption in suppliers. The proposed multi-objective mathematical model in this paper is a mixed-integer programming (MIP) model with objective functions to minimize transaction costs of suppliers, expected costs of purchasing goods, expected percentages of delayed products, expected returned products, and to maximize expected evaluation scores of the selected suppliers. Due to the uncertainty of demand and supplier disruption in the real world, their values are also considered uncertain; the proposed multi-objective model is studied by using a scenario-based stochastic programming (SP) method. In this method, all possible predictions for demand and disruption values are simultaneously included in the model; objective function results have more optimal value than a separate solution of the model for each predicted value

Technology progress in automotive sectors in term of eco-friendly and energy efficient vehicles

This paper mainly intended to highlight the importance of sustaining the technology of eco-friendly vehicles. This paper starts with a history of energy exploitation by a human being. The transition of energy source exploitation is running thru from the early renaissance time until this modern era of industrial revolution 4 (IR4.0). The internal combustion engine, in general, has served the world since early 20th -century driving until now. The depletion of oil reserves and the need to retain a green environment indicate the utmost important action must be taken to find an alternative source for new energy. This paper also highlights the concept technology cycle which in general, internal combustion engine technology has to reach the maturity stage, and innovation is needed to keep the engine technology up to date and create less pollution at the same time. Also, this paper reviews the factors that will drive towards technology innovation and the progress of the eco-friendly vehicle

An integrated production-distribution planning in green supply chain: a multi-objective evolutionary approach

The goal of this research is to develop a novel multi-objective mathematical model in a green supply chain network consisting of manufacturers, distribution centers and dealers in an automotive manufacture case study. The main objectives considered are: minimizing the costs of production, distribution, holding and shortage cost at dealers as well as minimizing environmental impact of logistic network. In addition to minimizing the costs and environmental impacts particularly the emission of CO2, the model can determine the green economic production quantity using Just-In-Time logistics. Furthermore, multi-objective genetic algorithm is applied in order to minimize these two conflicting objectives simultaneously. Finally, the performance of the proposed model is evaluated by comparing the obtained Pareto fronts from Moga and goal attainment programing solver in Matlab

A closed-loop supply chain network in the edible oil industry using a novel robust stochastic-possibilistic programming

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