پژوهشنامه بازرگانی
پیاپی 66 (بهار 1392)

Nowadays, production/distribution/inventory management as supply chain management system has replaced the traditional inventory management systems based on empirical decision of the manager. In the past half century, several mathematical tools have been used in modeling and control of supply chain management issue. In regard to advantages of model-based predictive control (MPC) in dealing with control of multivariable systems and its online structure, this method is efficient for utilization on inventory management systems. In this article, a predictive control with strategies to increase the robustness of production/distribution/inventory management is used, and a separate control is designed for any echelon till an initial ensure for centralized control is achieved. Robustness mechanisms are also studied in simulations.

Due to the importance of distribution planning among the different parts of the supply chain, in this paper we have considered the routing of transportation of goods between the various components of the supply chain as vehicle routing problem. The purposes of this paper are considering the real-world operational constraints of distribution planning and provide an efficient metaheuristic solution than other existing methods. Therefore in this paper the routing problem, includes a fleet size and mixed vehicles that are located in central depot and the possibility of split service and limited vehicle access availability for some costumers has been considers. The number of vehicles of each type is not limited. This problem is a well-known NP-hard one; therefore, a new multi-ant colony optimization algorithm is proposed to solve the given problem. Finally, the numerical results of designed experiment problems according to distribution network inside Iran with an improved heuristic method have been analyzed.

Establishing spot markets, mediator firms make advance contract with suppliers to provide commodity for a specific time and decreasing the risk. Then, they use spot market when facing shortage or surplus commodity. In contrast with advanc contracts, spot market prepares little delivery time, but it imposes uncertainty in price to the buyer. In this paper, such exchanges are considered in the case of discount to determine the optimum number of purchase and to decrease the risk of retailer. The developed mathematical model is based on profit function of the buyer, and risk avesion of the buyer is considered as profit variance. To evaluate the discount, a function that predicts the discounts continuously has been used and the analysis of parameter sensitivities has been discussed with a numerical example. The results indicate that increasing the risk aversion of retailer, optimum amount of purchasing leads to the average demand; this amount is also significantly different according to the relation between the price of the contract and spot market.

The procedure of Supply Chain Management to deal with perishable products has got noticeable attentions of scholars. For managing these products Cold Chain Management (CCM) came into sight. Special consideration to these goods and condition of market competition make a challenge to create the new method for Cold Chain Management Performance appraisal. First, this paper determined 40 main factors that are effective in CCM improvement and then by using Factor Analysis Approach 7 new latent variables emerged. The result shows that the equipment, planning and time respectively are The most important factors for Cold Chain performance improvement. Finally, future research suggestions have been given.

With increased pressures on environmental issues, enterprises have to implement strategies to reduce the environmental impacts of their products and services. They have to implement environmental management strategies. To establish their environmental image, enterprises need to re-examine the objectives of their business. Success in addressing environmental items may provide new opportunities for competition, and new ways to add value to core business programs. Approaches, such as cleaner production, environmental management systems and eco-efficiency, have been implemented for green management practices. Green supply chain management plays a key role in ensuring that all of these factors are addressed. Environmental impacts occur at all stages of a product’s life cycle. Therefore, Green supply chain management has appeared as an important component of business activities to help organizations develop ‘win-win’ strategies that achieve profit and market share objectives by lowering their environmental risks and impacts, while raising their ecological efficiency. The main aims of this study is identifying the main measurement items of the green supply chain management, designing a model and selecting the best green supplier. The study was conducted in two phases. In the first phase, factors of green supply chain were extracted from the literature and industry experts and a six-factor model was designed. In the second phase, on the basis of extracted factors, we used AHP technique and Grey theory for selecting the best green suppliers for the company.

Dynamic modeling and simulation of complex economic systems are new technologies with many applications in analysis and performance improvement of economic systems. In economic systems with nonlinear nature, uncertainties, lack of structural transparency, necessity to enter the cause and effect variables and proficiency knowledge are among the most noticeable issues. The following considerations, discusses the system dynamics method (dynamic modeling) as a proper tool for modeling, simulation and predicting behavior of these systems. this paper reviews the behavior of the steel market using the systems dynamic system. Based on the cause and effect diagram which extracted in previous stage, the flow diagram was presented. The data which was available in databases of different public organizations was used to simulate the real world and predicting the behavior of steel market. Moreover, with changing the related variables in model the behavior of the model was Reviewed (sensitivity analysis). Using these results the effects of the ministry of commerce policies for realization of market adjustments is analyzed. Because of economic Structure of The government, Ministry of Commerce has always been the custodian of the market adjustments. Preventing the fluctuations of supply chain and market adjustments are considered one of the duties of this ministry. This study will help in removing barriers and presenting new innovative solutions for using scientific approaches based on system analysis in different governmental sectors.

The general trend to focus more on core competencies has forced companies to use outsourcing strategies and led to appearance of supply chain. Supply chain risks can arise from many sources, including political events, demand fluctuation, technological changes, financial instability and natural disasters. To be able to handle these risks, supply chain risk management is needed. Managing supply risk is an essential part of the supply chain risk management and in this research we focus on supply risk management. We use value at risk, extreme value theory and cash flow at risk to present a method for quantification of supply risks such as late delivery, quality risk, natural disasters risk and business risk (financial instability of suppliers). Furthermore, a model for supplier selection and order allocation based on these supply risks, has been proposed. Finally, a numerical example is presented and some computational result is reported.