Nowadays, selecting the most appropriate location for hub is one of the most significant issues not only in road, rail and air transportations, but also in maritime. Transshipment is the fastest growing segment of the marine container market; it increases traffic flow of marine container and scope of this type of marine carriage, accordingly. In this way, determining a movement loop for the voyages of a shipping company, probes identification of container hub ports by considering different operational factors including distance to the destinations. The focus of this paper is to locate the best location for container transshipment hub in southern seas of Iran. In this paper, an MCDM model is proposed for evaluating and selecting the marine container transshipment hub port. Finally, the utilization of the proposed model is demonstrated with a real case study of Iranian main ports. The results show that the MCDM model can be used to explain the evaluation and decision-making procedures of a proper marine container hub location selection.

An important function of the project management is to optimize the project in various phases and at different levels. From sourcing and allocation to scheduling and even dealing with uncertainties, the science of operation research (OR) has played an important role in this area. So far, many papers have been published using the optimization science to make various decisions regarding the project management. This study aims to investigate all papers published on the application of optimization in the project management from 1940 to 2019 and shows: a) how the trend has changed over this 79 years period, b) to what direction the trend has changed, c) determines the interesting topics of the recent years, and d) which subjects are more attractive as future studies as the applications of the optimization techniques in the project management.

The numerous studies on comparing and ranking fuzzy numbers clear that this task is still young. However, the observation that many papers do not hesitate to use some incorrect ranking methods in risk analysis problems, encouraged the author to point out the shortcoming of some of these methods. In this note, we review briefly the methods for ranking fuzzy number in risk analysis.

Project portfolio selection is a major issue in organizations, which involves a complex pro-cess from the first step to the end step of project selection. In order to pursue the organizations’ financial and physical constraints, choosing the most suitable portfolio of projects is necessary. Organizations have a number of constraints to select a portfolio of projects that must be considered. Different interactions are considered between the proposed projects. For example, resource constraints, the possibility of transferring liquidity resources that are not consumed over a period to the next, the interdependence between projects, and the synergistic impact of the projects are important. In this paper, an exponential function is considered for synergistic impact of the projects that make the problem more similar to the real-world problems. An illustrative example is used to demonstrate the appropriate application of the proposed model.

Reliability is one of the most important characteristics of the electrical and mechanical systems with applications in the space communication industries, internet networks, telecommunication systems, power generation systems, and productive facilities. What adds to the importance of reliability in these systems are system complications, nature of competitive markets, and increasing production costs due to failures. This paper investigates availability optimization of a system using both repairable and non-repairable components, simultaneously. The availability-redundancy allocation problems involve the determination of component availability (i.e., life time and repair time of the components) and the redundancy levels that produce maximum system availability. These problems are often subject to some constraints on their components such as cost, weight, and volume. To maximize the availability and to minimize the total cost of the system, a new Mixed Integer Nonlinear Programming (MINLP) model is presented. To solve the proposed model, an improved version of the genetic algorithm is designed as an efficient meta-heuristic algorithm. Finally, in order to verify the efficiency of the proposed algorithm, a numerical example of a system is presented that consists of both repairable and non-repairable components.

The purpose of the present study is to investigate the inter-relationship among the indices that influence on knowledge sharing systems in lessons learned systems. To do this, while reviewing the literature, the researchers first identified the indices affecting KSS; then, they collected the related data through the use of a researcher-devised questionnaire. The results of surveying the indices of knowledge sharing system based on DEMATEL system analysis indicated that there were systemic relationships with the predominant characteristic of impressibility among the indices of the system. Investigating the internal relationship among the indices of knowledge sharing in learned lessons systems showed that in order to create a positive as well as optimum effect on knowledge sharing processes, the first priority should be updating and reinforcing “communication channels”; also, “reward systems and processes” should be reinforced as the second priority in line with the strengthening of the purposeful process of knowledge sharing system.

The design of supply chain networks has attracted more attention in recent years according to business and environmental factors.in this paper a multi objective supply chain network design model aims to minimize network costs while satisfying the desired service level, is presented. A fuzzy goal programming (FGP) solution approach based on fuzzy membership function concept is developed to minimize costs and amount of investment while obtain maximum service level. Numerical experiments are conducted to test the efficiency of proposed solution method.

Technology transfer, from research and technology organizations (RTOs) toward local industries, is considered as one of important and significant strategies for countries & apos; industrial development. In addition to recover the enormous costs of research and development for RTOs, successful technology transfer from RTOs toward local firms forms technological foundations and develops the ability to enhance the competitiveness of firms. Better understanding of factors influencing process of technology transfer helps RTOs and local firms prioritize and manage their resources in an effective and efficient way to maximize the success of technology transfer. This paper aims to identify important effective factors in technology transfer from Iranian RTOs and provides a comprehensive model, which indicate the interactions of these factors. In this regard, first, research background is reviewed and Cummings and Teng’s model (2003) [Cummings, J. L., & Teng, B.-S. (2003). Transferring R & D knowledge: The key factors affecting knowledge transfer success. Journal of Engineering and Technology Management, 20(1-2), 39-68.] was selected as the basic model in this study and it was modified through suggesting new factors identified from literature of inter-organizational knowledge and technology transfer and finally a Delphi method was applied for validation of modified model. Then, research conducted used Interpretive Structural Modeling (ISM) to evaluate the relationship between the factors of final proposed model. Results indicate that there were twelve factors influencing on technology transfer process from Iranian RTOs to local firms and also the intensity of absorption capability in transferee could influence on the intensity of desorption capability in transferor.

Flow-shop problems, as a typical manufacturing challenge, have become an interesting area of research. The primary concern is that the solution space is huge and, therefore, the set of feasible solutions cannot be enumerated one by one. In this paper, we present an efficient solution strategy based on a genetic algorithm (GA) to minimize the makespan, total waiting time and total tardiness in a flow shop consisting of n jobs and m machines. The primary objective is to minimize the job waiting time before performing the related operations. This is a major concern for some industries such as food and chemical for planning and production scheduling. In these industries, there is a probability of the decay and deterioration of the products prior to accomplishment of operations in workstation, due to the increase in the waiting time. We develop a model for a flowshop scheduling problem, which uses the planner-specified weights for handling a multi-objective optimization problem. These weights represent the priority of planning objectives given by managers. The results of the proposed GA and classic GA are analyzed by the analysis of variance (ANOVA) method and the results are discussed.

Quality of services in banking industry plays essential role in measuring the performance of banks. As customer awareness increases on the services offered by banks, expectations from service quality increases too. Presently, managers of banks use different financial factors such as deposits, credits, etc. to rank their banks. This paper uses SERVQUAL technique to measure customer satisfaction for 14 branches of a bank in city of Kermanshah, Iran. The study first statistically shows that customer satisfaction was not the same for all these banks and then using analytical hierarchy process and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) ranks these branches using five components of SERVQUAL method; namely tangibles, reliability, assurance, responsiveness and empathy.