Organized retailing (OZR) is one of the most promising industries in India. The OZR sector of India is now among the top five fastest growing markets of the world. High population, globalization, and the increasing income of middle class etc. are a number of factors that make Indian market more challenging and competitive. In today’s globalized world, effective supply chain performance (SCP) is highly important to ensure the productivity in the whole supply chain (SC). In this paper, we investigated the factors that affect cold supply chain performance (CSCP) of organized farm products retailing (OFPR), developed and validated a model. This research will be helpful to formulate better strategies for this sector to a greater extent; this model will also be useful and applicable for other developing Asian countries because of enormous similarities in their market tendencies.
In this paper, an integrated production-inventory model with multi-item is developed from the perspectives of single producer, multiple suppliers and retailers. In this three-layer supply chain, the retailers are non-competing. Every supplier delivers only single type of raw material to the producer. The producer manufactures finished goods from the combination of fixed percentage of different types of raw materials. The producer manufactures various types of objects and supplies them to retailers according to the demand of multiple retailers. This paper studies the impact of different types of business policies such as exponential demand rate, demand dependent production rate, optimum order size of raw materials, and unit production cost at each stage of integrated marketing system. Mathematica is used to develop the model and to optimize the integrated profit function. A numerical example and sensitivity analysis is illustrated to justify the feasibility of the proposed model.
This paper presents an empirical investigation to determine important business intelligence factors influencing on development of export activities. The study selects a sample of business developers who were involved in export activities in city of Tehran, Iran. Cronbach alpha based on standardized items was calculated as 0.882, which is well above the minimum desirable level. In addition, Bartlett & apos; s test of Sphericity yields a Chi-Square value of 3242.82 (df = 861, Sig. = 0.000). Using principle component analysis, the study has determined four factors including competitive position, organizational resources, efficient system and customer orientation influencing on development of export activities.
Having a supply chain is an unavoidable fact and all companies should focus on if they wish to survive in the competitive business world. This paper ranks criteria influencing on behavior of a medicine manufacturer agent when its goal is to select the supplier agents to interact with across a pharmaceutical agent based supply chain. The pharmaceutical industry is important for countries due to the distinguished role of health in societies and Iran is not an exception too. Besides, the industry in this country is encountered with some limitations because of the situation imposed by sanctions. In this study, first, ten criteria were selected based on expert’s opinions, two categories of quantitative as well as qualitative criteria were chosen for ranking the criteria and then TOPSIS and PROMETHEE ? methods were applied to rank the criteria. According to the results of this survey, qualitative criteria were determined as important factors influencing on supplier selection.
In supply chain management, supplier performance is evaluated based on several criteria. In this paper, a fuzzy multi-objective mathematical programming model is presented to consider different qualitative and quantitative factors to choose appropriate suppliers and the optimal order quantity allocated to them. The proposed study uses analytical hierarchy process to rank different suppliers and a fuzzy multi-objective mathematical programming is presented to choose the best suppliers. The study uses NSGAII to solve the resulted problem and the model is analysed using some sample results under various circumstances. The study considers different Pareto solution set obtained by TOPSIS ranking algorithm, and eventually determines the best possible solutions.
Inventory planning for the pre- and post-disaster phases of disaster relief lifecycle is a challenging problem associated with the humanitarian relief supply chains. In this work, two mathematical models are presented encompassing the whole disaster relief lifecycle. By accounting for holding costs of perishable supplies, a two-stage stochastic programming model is first developed by which the inventory prepositioning locations, inventory levels, and short-term distribution quantities are determined. For the recovery phase, this research adapts the well-known continuous review (Q, r) inventory model for relief warehouses while accounting for the inherent epistemic uncertainty in the required data by using the fuzzy programming. A case study of Iranian Red Cross is also provided to illustrate the applicability of the first model and to demonstrate how it supports the two first phases of disaster lifecycle. Additionally, a numerical example is presented to demonstrate the applicability of the (Q, r) model for the recovery phase. Lastly, the impact of penalty costs on the solutions is discussed.
Mining is one of the most important sectors in most countries. It produces raw material for other sectors such as industry, agriculture, etc. Therefore, governments always seek the solutions to prevent or at least reduce the risk of mining industry to minimize the waste of time and resource. One of the most popular risk in mining industry that should be clearly assessed is supply chain. There is a variety of methods to evaluate and classify risks. Fuzzy set is one of the most appropriate methods to categorize and evaluate risks, because this method is able to take into account the uncertainty involved in the process of risk assessment. In this article, fuzzy inference system is applied to evaluate and assess the supply chain risk of the Iranian mining industry. This research shows that the proposed model had a high accuracy and efficiency for assessing the risk of mining industry.
Today, due to rapid changes in the world, the infrastructure should be designed to produce goods in world class. Dynamic layout planning increases flexibility and reduces the cost of new products. Investigating the essential factors to achieve world-class shows that dynamic layout planning plays essential role on flexibility, cost reduction, implementation of world-class producing techniques, reduction of product delivery time, customer satisfaction, and management in multiple and worldwide locations. The purpose of this study was to investigate the role of dynamic layout planning on production of world class products in some firms located in province of Zanjan, Iran. Using Spearman correlation test, the study indicated that dynamic layout planning played an important role in delivering the products to the world-class level.
Energy crisis in recent decades has demonstrated strong interdependence between national security and energy security. We are also witness of sever conflicts in oil-rich zones such as Middle-East and West of Suez. This study is the first attempt to provide a flexible multi-objective mathematical model which not only mitigates catastrophic risks by filtering and taking plausible oil-supply disruption scenarios into account, but also reduces oil-supply disruption probability by considering and optimizing political, economic and financial dimensions of oil procurement. Mentioned model determines a resilient portfolio of oil suppliers under each scenario and decides which ports or pipelines must be prepared for receiving oil. Furthermore, the proposed model in the second phase enhances oil-availability in crisis time by storing strategic oil stocks in appropriate geographic points. Also regarding to complexity of the second phase model, a meta-heuristic algorithm has been provided to solve the mentioned model. Finally validity of proposed model is checked by solving it for Greece case problem; sensitivity analysis shows that provided model significantly mitigates catastrophic risks threating energy security by balancing political affairs and reinforcing infrastructural facilities with the least possible cost.
In this paper, we evaluate the performance of a supply chains (SCs) under uncertainty with different components such as direct costs, operational costs, transaction expenses, order lead time, product flexibility and net profit. Data Envelopment Analysis (DEA) can be used for measuring the performance of supply chain problems. On the other hand, robust optimization approach is a powerful technique for handling problems faced with various environmental uncertainties. This paper combines these two concepts and proposes a method to evaluate SCs performance. The results of the proposed method, under any different environmental situation, show which ranking of SC’s performance is better in a network. The preliminary results of the implementation of a real-world case study indicates that the method could be successfully used for performance measurement.