A closed-loop supply chain network in the edible oil industry using a novel robust stochastic-possibilistic programming

In recent years, the complexity of the environment, the intense competition of organizations, the pressure of governments on producers to manage waste products, environmental pressures and most importantly, the benefits of recycling products have added to the importance of designing a closed loop supply chain network. Also, the existence of inherent uncertainties in the input parameters is another important factor that the lack of attention them can affect the strategic, tactical and operational decisions of organizations. Given these reasons, this research aims to design a multi-product and multi period closed loop supply chain network model in uncertainty conditions. To this aim, first a mixed-integer linear programming model is proposed to minimize supply chain costs. Then, for coping with hybrid uncertain parameters effectively, randomness and epistemic uncertainty, a novel robust stochastic-possibilistic programming (RSPP) approach is proposed. Furthermore, several varieties of RSPP models are developed and their differences, weaknesses, strengths and the most suitable conditions for being used are discussed. Finally, usefulness and applicability of the RSPP model are tested via the real case study in an edible oil industry

Demand forecasting in a Supply Chain using Machine Learning Algorithms

Abstract—the purpose of this paper is to compare two artificial intelligence algorithms for forecasting supply chain demand. In first step data are prepared for entering into forecasting models. In next step, the modeling step, an artificial neural network and support vector machine is presented. The structure of artificial neural network is selected based on previous researchers' results. For measuring errors we use Mean squared error and we use another index for time which is used running the algorithms. The results show that artificial neural network can forecast more accurate meanwhile support vector machine is faster

An Integrated Fuzzy Model for Selecting Resilient Suppliers in Electronics Industry of Iran

Selecting appropriate and resilient suppliers is an important issue in supply chain management (SCM) literature. Making an effective decision on this issue can decrease external risks and disruptions, purchase costs, and delay times and also guarantees business continuity in the event of disruptions and, consequently, increases company competitiveness and customer satisfaction. This paper aims to provide a model based on identifying and investigating related criteria to evaluate suppliers’ resilience and select the most resilient suppliers in Iran’s electronic industry. To this purpose, the screening technique, the best-worst methodology (BWM), and goal programming (GP) have been applied in the fuzzy environment. The proposed model has been implemented and demonstrated by a case study of the electronic industry, as a real-life example. The results show that agility (0.227), compatibility (0.153), and vulnerability (0.102) are the most important factors for a resilient supplier

A hybrid algorithm for unrelated parallel machines scheduling

In this paper, a new hybrid algorithm based on multi-objective genetic algorithm (MOGA) using simulated annealing (SA) is proposed for scheduling unrelated parallel machines with sequence-dependent setup times, varying due dates, ready times and precedence relations among jobs. Our objective is to minimize makespan (Maximum completion time of all machines), number of tardy jobs, total tardiness and total earliness at the same time which can be more advantageous in real environment than considering each of objectives separately. For obtaining an optimal solution, hybrid algorithm based on MOGA and SA has been proposed in order to gain both good global and local search abilities. Simulation results and four well-known multi-objective performance metrics, indicate that the proposed hybrid algorithm outperforms the genetic algorithm (GA) and SA in terms of each objective and significantly in minimizing the total cost of the weighted function

A framework for online social networking features

Social networks form a basis for maintaining social contacts, finding users with common interests, creating local content and sharing information. Recently networks have created a fundamental framework for analyzing and modeling the complex systems. Users' behavior studies and evaluates the system performance and leads to better planning and implementation of advertising policies on the web sites. Therefore, this study offers a framework for online social networks' characteristics. In terms of objective, this survey is practical descriptive. Sampling has been done among 384 of graduate students who have good experiences of membership in online social network. Confirmatory factor analysis is used to evaluate the validity of variables in research model. Characteristics of online social networks are defined based on six components and framework's indexes are analyzed through factor analysis. The reliability is calculated separately for each dimension and since they are all above 0.7, the reliability of the study can be confirmed. According to our research results, in terms of size, the number of people who apply for membership in various online social networking is an important index. In terms of individual preference to connect with, people who are relative play essential role in social network development. In terms of homogeneity variable, the number of people who visit their friends’ pages is important for measuring frequency variable. In terms of frequency, the use of entertainment and recreation services is more important index. In terms of proximity, being in the same city is a more important index and index of creating a sense of belonging and confidence is more important for measuring reciprocity variable

The Effect of Human Resources Information Systems on Knowledge Sharing Through the mediation of Organizational Culture (The Case of Branches of Mellat Bank in Shiraz City)

The main purpose of this study is to investigate the effect of human resources information systems on knowledge sharing through the mediation of organizational culture in Branches of Mellat Bank in Shiraz city. In this study, the key indicators for each variable of the study (human resources information systems, knowledge sharing and knowledge-based organizational culture) was given. then, they surveyed by comments of professors and experts in the field of information systems and knowledge management. Research tools were questionnaire and interview. After random samplingو questionnaire distributed and collected between 118 managers and assistants of brances.Finally, hypothesis were tested by path analysis. The results showed that human resources information systems had a significant impact on knowledge sharing. As well as, knowledge-based culture had a significant effect on knowledge sharing. In addition, the findings showed that the human resources information systems can assist managers in selecting the best individual in a right time for training and this can improve knowledge sharing within the organization. And knowledge-based organizational culture can improve mutual trust between organizational members and this can increase the sharing of knowledge in the organization

Optimal level of demand and supply public goods in the general equilibrium model with Lindahl tax

In the real world, there are commodities that although consumers are willing to pay for them, but they cannot obtain them by market. These goods are public goods that all people will benefit from their use, and about them so-called market fails. One of indicators for evaluation the performance of government is amount of production of public goods. In this regard, the optimal level of the production of public good that maximize households’ utility is very important. In this article, three sections are as follows; households, firms and government-monetary authorities, due to the limitations that each section is faced, each of them is looking to optimize its goals. The results of the optimization household utility function show the optimal level of public good demand that it is proportional to pay people as taxes. Also the results of production function of public good show the optimal level of supply of public goods and services. Compare the optimal amount of demand and supply of public good show that there is a huge gap between optimal levels

A Combined Approach of FMEA and Gray Theory to Rank Aspects of Information Security Risk Management

The study conducted with aim of ranking each aspect of information security risk management. At the first stage, the dimensions and characteristics of each have been identified based on the research literature and expert opinions. In order to rank the factors under study using a hybrid approach using FEMA and Gray theory, 50 questionnaires collected among IT, soft ware, and network experts that choosed based on researchers’ judgement and accessible one. According to the results, the security of communications was ranked first. Infrastructure of hard ware and network, human factors, security management, access to information and systems and the development of secure information systems were ranked second to sixth, respectively.Therefore, it is recommended that organizations set up an independent security department within the organization. Also, providing a list of all the information assets of the organization and specifying control and strategic goals in the area of information security in the organization can be useful for organizations. Moreover, if the organization has several branches and need internet connection, preferably communications are available as VPN. In addition, if organizations have web automation for outside usage, the site should be licensed with SSL and https protocol