The life of many people in the world is under the danger because of the accidents and unpredicted diseases, which require relief. Since, most of such cases occur in unpredictable condition, for an appropriate planning, the uncertain conditions should be investigated. Consequently, this paper investigates the INTEGRATED and multi-step process of locating, assigning and routing the air and land emergencies in the uncertain conditions in order to reach the stable solution that faces minimum changes against different conditions. In the presented model, the emergency demand is defined in the stochastic and fuzzy environment in order to show the actual conditions. The findings indicate that the models intend to create an optimum balance between cost minimization and increasing the demand satisfaction rate. However, in general conditions, the decisions should be made considering the exisitng conditions.

In this paper, a hybrid multi-criteria decision-making (MCDM)-method and mixed integer linear programming (MILP) approach in order to evaluation of the returned products' collectors along with their ordered quantities, is utilized. Firstly, the most important criteria of collection center in the car industry are identified. Then, in order to evaluate these proposed criteria, a hybrid Fuzzy Decision-Making Trial And Evaluation Laboratory (FDEMATEL)-evaluation of mixed qualitative and quantitative data (EVAMIX) approach is applied. By this method, the most important criteria and their weights along with collection centers' score are determined. In addition, an MILP mathematical model is proposed for selection of the best collection center and computation of ordering quantities. An efficient approach for collection center selection and a novel application of combined FDEMATEL, EVAMIX, and MILP model can be considered as the main contributions of this paper. It should be noted that, to measure the performance of this method a recycling company as a case study in Iran has considered which of this firm collects effete tire and ball bearings of cars. Implementation of this case study can be considered as the other contributions of this paper. At last, with help of obtained results the proper collection center and their ordered quantities are computed. In addition, for measure efficiency of the proposed model, some numerical example, in various dimensions is considered. Moreover, the managers of this industry with the help of a simple methodology can choose the appropriate suppliers.

One of the fundamental points in every research is considering history, fields& evolution of the subject which is known as literature review. Thus in order to study LOGISTICS it is essential to review conceptual& historical evolution surveys, logistic theories& concepts. Furthermore, a suitable perspective& approach should be acquired.Studying books, articles & researches demonstrates different paradigms have been developed in logistic field. There for, this paper attempts to review serous logistic paradigms. At the end, integneted logistic paradigm is presented for future researches.

This study aimed to determine by measuring the extent to which INTEGRATED Reporting Framework content element is linked to value creation. The sample of the LOGISTICS industry study was gathered from INTEGRATED Reporting Examples Database. Sentence-by-sentence content analysis was conducted on 11 INTEGRATED reports of LOGISTICS companies using a multi-weighted scoring tool and an INTEGRATED Reporting Value Creation Checklist (IRVC) based on the literature and the International INTEGRATED Reporting Council (IIRC) INTEGRATED Reporting (IR) framework. Additionally, descriptive statistics were performed for subtitles of IRVC, Value Creation Scores, and the INTEGRATED Report Specific Feature Scores. In the end, IR content disclosures of LOGISTICS companies were presented. The scoring results of the Content Analysis were interpreted in terms of each content element and each company scores. Additionally, descriptive statistics were applied for IRVC scores. The findings indicated that content items were highly aligned with value creation links, with the highest scores being determined in “business model” and the lowest scores in “performance, ” “outlook, ” and “risks and opportunities. ” In addition, it has been observed that there are noticeable differences among the company value creation scores in the current practice.

Design of a LOGISTICS network in proper way provides a proper platform for efficient and effective supply chain management. This paper studies a multi-period, multi echelon and multi-product INTEGRATED forward-reverse LOGISTICS network under uncertainty. First, an efficient complex mixed-integer linear programming (MILP) model by considering some real-world assumptions is developed for the INTEGRATED LOGISTICS network design to avoid the sub-optimality caused by the separate design of the forward and reverse networks. Then, the stochastic counterpart of the proposed MILP model is used to measure the conditional value at risk (CVaR) criterion, as a risk measure, that can control the risk level of the proposed model. The computational results show the power of the proposed stochastic model with CVaR criteria in handling data uncertainty and controlling risk levels.

We investigate a closed-loop supply chain in this article that manufacturer has two channels for satisfying the demand: producing brand-new products or remanufacturing returned items. There is no difference between brand-new products and returned one so they can be sold at the same market with the same price. In this article, demand has price sensitive uncertainty. Also returns are stochastic and price sensitive too. In addition we define acceptance quality level for acquiring returned products. Therefor a mathematical model developed to maximize total profit of system that determines selling price, production quantity of brand-new products and remanufactured one, acquisition price and minimum acceptance quality level for returned items.

In many industries, manufacturers for various reasons, have to collect products are used by customers. Then, depending on the situation returns, required to process the decision taken on the product. In this paper the problem of optimizing inventory control and product planning in the environment has been INTEGRATED reverse LOGISTICS. LOGISTICS network to consist of two stages. In the first stage returns using the qualitative thresholds defined, separated and sent to the appropriate lines recovery or disposal, are subject to quality inspection. In the second stage having different amounts sent to the line, a mixed integer optimization algorithm (MILP) to lower the total cost of our network. Model with a view to minimizing the costs, the type of problems that are NP-Hard, the problem increases exponentially. Therefore, in this study, Genetic Algorithm is used to solve the model.

In today's world, economic climate changes more quickly, and countries realize that globalization has made the world smaller and more competitive. Also, customers seek products and services that can respond to their specific needs and firms make effort to create competitive advantages to keep their profit and market share. All of the above trends lead firms and countries to focus on supply chain and INTEGRATED LOGISTICS. Making supply chain activities more effective and efficient is a sustainable competitive advantage for countries. One of the important parts of these activities is LOGISTICS activities, which can make a significant reduction in costs. Efficient management of LOGISTICS activities is a perfect source for creating competitive advantages. Besides, it allows firms to respond to their customers' specific needs, which in turn, results in customer satisfaction. Because designing the forward and reverse LOGISTICS network separately leads to sub-optimality, one of the proper areas to achieve more efficiency in LOGISTICS network is to design forward and reverse LOGISTICS network simultaneously. This paper proposes a MINLP model for INTEGRATED LOGISTICS network design to avoid the sub-optimality caused by a separate, sequential design of the forward and reverse networks. The proposed model could support multi-level capacity for each facility and also consider saving costs associated with locating the distribution centers and collection/inspection centers in the same places. To escape from the complexity of the proposed MINLP model, the model is made linear by defining a new variable and adding a constraint to the model. Since such network design problems belong to a class of NP-hard problems, we propose an efficient memetic algorithm with dynamic local search mechanism and we compare the associated numerical results by exact solutions in a set of problems to present the high-quality performance of the proposed algorithm. Future research could be aimed robust models to accommodate the changing parameters of the business environment during the life-time of the LOGISTICS network. Also addressing the demand uncertainty and the supply of return products in a multi-product INTEGRATED LOGISTICS network is a promising research avenue with significant practical relevance. Although our memetic dynamic search strategy proved to be competitive for the IFRLN network problem under consideration, other meta-heuristics algorithms such as tabu search or scatter search could offer promising avenues for developing richer INTEGRATED LOGISTICS networks as well.