Facility location models are observed in many diverse areas such as communication networks, transportation, and distribution systems planning. They play significant role in supply chain and operations management and are one of the main well-known topics in strategic agenda of contemporary manufacturing and service companies accompanied by long-lasting effects. We define a new approach for solving stochastic single source capacitated facility location problem (SSSCFLP). Customers with stochastic demand are assigned to set of capacitated facilities that are selected to serve them. It is demonstrated that problem can be transformed to deterministic Single Source Capacitated Facility Location Problem (SSCFLP) for Poisson demand distribution. A hybrid algorithm which combines Lagrangian heuristic with adjusted mixture of Ant colony and Genetic optimization is proposed to find lower and upper bounds for this problem. Computational results of various instances with distinct properties indicate that proposed solving approach is efficient.

The rise in the worldwide demand of forest products of the last decades predicts an expansion of the forest harvesting industry. In this context, the Argentinian Northeastern Region (NEA) is considered a promising land since the local forest harvesting industry has one of the largest growing rates in the world. Despite its potential, this region faces some challenging obstacles: budget shortage, trade barriers and poor logistic infrastructure. For instance, traditionally the forest products are delivered by truck, which is from three to five times more expensive than other means of transport, like maritime or river transport. This is why in this paper, after a revision of the most recent advances in the worldwide supply chain management practices in the forest industry, recommendations for Argentina in order to overcome its main drawbacks in the forest sector are presented.

In this paper, we design a revenue sharing contract to coordinate pricing and inventory control decisions in a serial supply chain consisting of one supplier, one manufacturer and one retailer. We assume that the retailer faces Poisson demand and his unsatisfied demands will be lost. The retailer applies one-for-one period policy in which he constantly places an order for one unit of product to the manufacturer in a predetermined time interval which results in a deterministic demand for the manufacturer. Solution procedures are developed to find the equilibrium in the Vendor Managed Inventory (VMI) program with a revenue sharing contract, in which no party is willing to deviate from for the sake of maximizing his own profit. Furthermore, we formulate the total profit of the system and obtain the optimal retail price and order cycle for the retailer and the inventory policy of manufacturer which maximizes the supply chain’s total profit and at the end we will highlight the revenue sharing contract performance.

Vendor managed inventory (VMI) is one of the most effective methods for reducing bullwhip effect. This paper presents a mathematical VMI model where there are three levels of central storage, multi distribution centers and various retailors. The problem is formulated as a mixed integer programming by considering uncertainty on different input parameters. To cope with uncertainty, the study uses rectangular fuzzy numbers. We also propose two metaheuristics; namely, genetic algorithm and particle swarm optimization to solve the resulted problems for some large instances. The preliminary results have indicated that genetic algorithm could solve the proposed model faster than particle swarm optimization in terms of CPU time reaching to slightly better objective functions.

Fashion and Apparel Supply Chains work in a very fast-changing environment and always demand better quality, higher availability of products, broader assortments and shorter delivery times. An efficient Supply Chain Management can make a difference between success and failure in the market. In this context, the main purposes of the presented work are: (i) to define the physical and informative flows, together with connected cost and revenue items, which characterize a Fashion Supply Chain working with a wide network of direct-operated or franchising mono-brand stores and (ii) to optimize Supply Chain performances through a responsive approach which, during the sales season, analyses actual market demand and adjusts operations plans accordingly. The framework aims at becoming a decision support system for the optimization of the performances of a process that starts from the development of the collection by the Styling Office and ends with the withdrawal of unsold items from the stores. In order to analyze the performances under different scenarios, a set of Key Performance indicators, partially selected from the SCOR Model, is defined.

Nowadays the use of fossil fuels as a non-renewable energy source has become a major challenge because of the pollution and the environmental impact. Substitution of biomass as an energy source and its supply chain design is the main question. Because of difficulties such as supply chain complexity, uncertainty in variables and selecting the site of bio-refineries many studies have been conducted in this regard. Studies in the field of biomass and biofuel production are described and classified. Also the strategic decisions such as choosing the sites, selecting energy conversation technology, ensuring economic, environmental, technical, and social sustainability and tactical decisions including allocating resources to productive plants, selecting transport modes, and types of warehouses are addressed in the reviewed papers. We have reviewed 140 papers in the interval between 1997 and 2016 and classified them based on the objective functions. The articles are classified based on their being single or multi objectivity, linearity or nonlinearity. Finally, a classification based on the regions in which the studies have been done.

This paper presents a survey to identify and rank the supply chain management factors influencing the quality of the products for small and medium enterprises (SMEs) in food industry. The study designs a questionnaire in Likert scale and distributes it among 238 randomly selected managers of SMEs in food industry in city of Tehran, Iran. Cronbach alpha is calculated as 0.851, which is well above the acceptable level. Using principle component with Varimax rotation, the study has determined four important factors including strategic management, product management, manufacturing process management, organizational resources, customer orientation, industry capacity, which influence the most on product quality improvement.

This paper presents an empirical investigation to study the role of quality in supply chain management in development of brand equity. The study uses two questionnaires, one for measuring quality in supply chain adopted from Fynes et al. (2014) [Fynes, B., De Burca, S., & Marshall, D. (2004). Environmental uncertainty, supply chain relationship quality and performance. Journal of Purchasing and Supply Management, 10(4), 179-190.] and the other for measuring the brand equity, which was adopted from Buil et al. (2013) [Buil, I., De Chernatony, L., & Martínez, E. (2013). Examining the role of advertising and sales promotions in brand equity creation. Journal of Business Research, 66(1), 115-122.]. The survey has accomplished among auto part producers in Iran. The study selects 385 randomly selected people who were active in this industry. Using Spearman correlation ratio as well as Stepwise regression techniques, the study has concluded that there were positive and meaningful relationships between three supply chain factors, namely relationship, commitment and compatibility, and brand equity.

In the context of supply chain management, supplier selection plays a key role in reaching desirable production planning. In today & apos; s competitive world, many enterprises have focused on selecting the appropriate suppliers in an attempt to reduce purchasing costs and improve quality products and services. Supplier selection is a multi-criteria decision problem, which includes different qualitative and quantitative criteria such as purchase cost, on time delivery, quality of service, etc. In this study, a fuzzy multi-objective mathematical programming model is presented to select appropriate supplier and assign desirable order to different supplies. The proposed model was implemented for an organization by considering 16 different scenarios and the results are compared with two other existing methods.

Supply chain management plays essential role on improvement of the efficiency of production systems. It helps firms meet their expectations, deliver their products on time and build a good brand. This paper performs an empirical investigation to study the effect of good relationships among various suppliers on financial figures in an Iranian automaker. The proposed study investigates the effects of seven variables including communication, cooperation, commitment, compatibility, organization climate, dependency and trust on two financial figures including return on assets and return on equities. Using structural equation modeling, the study detects that communication, dependency and trust influence positively on return on assets. In addition, communication, cooperation, trust and commitment have positive impact on return on equities.