INTERNATIONAL JOURNAL OF APPLIED OPERATIONAL RESEARCH
Year:2013 | Volume:3 | Issue:3|Papers Count:8

In this paper, we investigate the fuzzy logic based system characteristics of MX/G/1 retrial queuing system with Bernoulli vacation schedule. The service time and vacation time are assumed to be generally distributed. It is found in many practical situations that the queuing models with fuzzy parameters are much more realistic than the classical crisp parameters based queuing models. We have chosen group arrival rate, service rate and vacation rate to be fuzzy parameters. The objective of this study in this paper is to transform MX/G/1 retrial fuzzy queue with Bernoulli vacation schedule to a family of conventional crisp queues by employing a-cut approach based on Zadeh’s extension principle. We formulate a pair of parametric non-linear programs (PNLPs) to describe the family of crisp queues with a vacationing server. To illustrate the validity of the proposed approach, the numerical examples are facilitated for different service time and vacation time distributions.

Facing supply uncertainty of bulky wastes, the capacitated multi-product stochastic network design model for bulky waste recycling is proposed in this paper. The objective of this model is to minimize the first-stage total fixed costs and the expected value of the second-stage variable costs. The possibility of operation costs and transportation costs for bulky waste recycling is considered while making the first-stage decisions about the network configuration. Integrating harmony search with sample approximation approach, a meta-heuristic is elaborated to solve the stochastic network design problem of bulky waste recycling, i.e. to decide where bulky waste recycling centers should be opened, and to determine which disposition procedure should be introduced. Several numerical examples are utilized to demonstrate the validness of the harmony-search-based sample approximation algorithm (HSSAA).In addition, the HS-SAA is compared to a genetic algorithm previously applied to the same problem. HS-SAA has advantages in the solution quality.

This paper develops an integer mathematical programming model to design the cellular manufacturing systems under data envelopment analysis. Since workers have an important role in doing jobs on machines, assignment of workers to cells becomes a crucial factor for fully utilization of cellular manufacturing systems (CMS). The aim of the proposed is to minimize backorder costs and intercellular costs. The Data Envelopment Analysis (DEA) is performed to determine the most efficient alternative among alternatives that considered by employing the average machine utilization, the average worker utilization, the number of product as the output variables and the number of machines, the number of workers, the number of parts and demand levels as the input variables. We are using the Tchebycheff norm method to rank the best DMUs.

This paper concerns with a mathematical model considering customer satisfaction requirements in a supply chain. The model tradeoffs the supply chain ability to fulfill the customers’ requirements and the limited budget in a variety of production phases. The decisions made here help to determine the profit provider price and economic quantity while the effective supplier and priori requirements are found. A numerical example illustrates the applicability of the proposed mathematical model.

Decisions in today's competitive and turbulent environments without access to information can confuse managers. The information system, which is planning, design and deployment as efficient and effective way, can help to improve the organization and create competitive advantage. One of the success factors and effectiveness of information systems in organizations is the organizational factors.In this research, organizational factors such as top management support, resource allocation, decisionmaking structure, management style and alignment of goals and knowledge of IT management, that affects the success factors of information systems (System quality, user satisfaction, perceived usefulness and quality of information), were analyzed and prioritized by Analytic Hierarchy Process (AHP) in Industries and Mines Organization of Isfahan Province. After gathering information and analysis by using the Expert Choice, it was found that among success factors of information systems, and user satisfaction is the most important factor, and the most important factor affecting success of organizational information system is the top management support.

This paper presents two meta-heuristic algorithms to solve an extended portfolio selection model. The extended model is based on the Markowitz's Model, aiming to minimize investment risk in a specified level of return. In order to get the Markowitz model close to the real conditions, different constraints were embedded on the model which resulted in a discrete and non-convex solution space.However, due to the NP-hard nature of the problem; two meta-heuristic algorithms were used, namely the simulated annealing and electromagnetic algorithms. Comparative result indicated high efficiency of the extended model and the solution presented by the electromagnetic algorithm.

This paper develops a bi-objective portfolio selection problem that maximizes returns and minimizes a risk measure called conditional Drawdown (CDD). The drawdown measures include the maximal Drawdown and Average Drawdown as its limiting case. The CDD family of risk functional is similar to conditional value at Risk (CVaR). In this paper, the fuzzy method has been used to solve the bi-objectives model. The relevance of the proposed model is illustrated by a real life portfolio selection.

Collection of waste is an important logistic activity within any city. In this study, a mathematical model is proposed in order to reduce the cost of waste collection. First a mixed-integer nonlinear programming model is provided including a waste collection routing problem, so that, there is a balance between the distance between trashcans, and the similarity of the trashcans in terms of the types of waste which is in the trashcans, in order to select the optimal route for each garbage transport vehicles. For this purpose, a similarity pattern is designed. Then, the model is solved by using LINGO 0.9 software and the output results of solved model were analyze.