IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2104 10.22034/2014.2.01 Research Paper Modelling the Level of Adoption of Analytical Tools; An Implementation of Multi-Criteria Evidential Reasoning Modelling the level of adoption of analytical tools; An implementation of multi-criteria evidential reasoning Barahona Igor Chapingo Autonomous University (UACh) , Carretera México, Texcoco de Mora, MEX, Mexico Cavazos Judith Popular Autonomous University of Puebla State. Puebla, Mexico Yang Jian-Bo Manchester Business School (MBS) 01 08 2014 1 2 129 151 10 10 2014 10 12 2014 Copyright © 2014, Kharazmi University. 2014 http://www.ijsom.com/article_2104.html

In the future, competitive advantages will be given to organisations that can extract valuable information from massive data and make better decisions. In most cases, this data comes from multiple sources. Therefore, the challenge is to aggregate them into a common framework in order to make them meaningful and useful.This paper will first review the most important multi-criteria decision analysis methods (MCDA) existing in current literature. We will offer a novel, practical and consistent methodology based on a type of MCDA, to aggregate data from two different sources into a common framework. Two datasets that are different in nature but related to the same topic are aggregated to a common scale by implementing a set of transformation rules. This allows us to generate appropriate evidence for assessing and finally prioritising the level of adoption of analytical tools in four types of companies.A numerical example is provided to clarify the form for implementing this methodology. A six-step process is offered as a guideline to assist engineers, researchers or practitioners interested in replicating this methodology in any situation where there is a need to aggregate and transform multiple source data.

MCDA methods Evidential Reasoning Analytical tools Multiple source data
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IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2047 10.22034/2014.2.02 Research Paper The Variance-covariance Method using IOWGA Operator for Tourism Forecast Combination The Variance-covariance Method using IOWGA Operator for Tourism Forecast Combination Wu Liangping College of Mathematics and Software Science, Sichuan Normal University, Chengdu, China. Zhang Jian Visual Computing and Virtual Reality Key Laboratory of Sichuan Province, Sichuan Normal University, Chengdu, China. 01 08 2014 1 2 152 166 21 07 2014 13 11 2014 Copyright © 2014, Kharazmi University. 2014 http://www.ijsom.com/article_2047.html

Three combination methods commonly used in tourism forecasting are the simple average method, the variance-covariance method and the discounted MSFE method. These methods assign the different weights that can not change at each time point to each individual forecasting model. In this study, we introduce the IOWGA operator combination method which can overcome the defect of previous three combination methods into tourism forecasting. Moreover, we further investigate the performance of the four combination methods through the theoretical evaluation and the forecasting evaluation. The results of the theoretical evaluation show that the IOWGA operator combination method obtains extremely well performance and outperforms the other forecast combination methods. Furthermore, the IOWGA operator combination method can be of well forecast performance and performs almost the same to the variance-covariance combination method for the forecasting evaluation. The IOWGA operator combination method mainly reflects the maximization of improving forecasting accuracy and the variance-covariance combination method mainly reflects the decrease of the forecast error. For future research, it may be worthwhile introducing and examining other new combination methods that may improve forecasting accuracy or employing other techniques to control the time for updating the weights in combined forecasts.

Tourism forecasts Forecast combination IOWGA operator Theoretical evaluation Forecasting evaluation
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IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2046 10.22034/2014.2.03 Review Paper A Literature Review on the Fuzzy Control Chart; Classifications & Analysis A Literature Review on the Fuzzy Control Chart; Classifications & Analysis Zavvar Sabegh Mohammad Hossein Kharazmi University, Tehran, Iran Mirzazadeh Ablofazl Kharazmi University, Tehran, Iran Salehian Saber Kharazmi University, Tehran, Iran Wilhelm Weber Gerhard Middle East Technical University,Ankara, Turkey 01 08 2014 1 2 167 189 02 08 2014 13 11 2014 Copyright © 2014, Kharazmi University. 2014 http://www.ijsom.com/article_2046.html

Quality control plays an important role in increasing the product quality. Fuzzy control charts are more sensitive than Shewhart control chart. Hence, the correct use of fuzzy control chart leads to producing better-quality products. This area is complex because it involves a large scope of industries, and information is not well organized. In this research, we provide a literature review of the control chart under a fuzzy environment with proposing several classifications and analysis. Moreover, our research considered both attribute and variable control chart by analyzing the related researches based on the content analysis method, to classify past and current developments in the fuzzy control chart. This work has included a distribution of articles according to the journal, the case studies related to fuzzy control chart, the percentage of types of fuzzy control charts used in the literature, performance evaluation of the fuzzy control chart and summary of key points of each review paper. Finally, this paper discusses some future research direction and our overviews. The results of this study can help researchers become familiar with well-known journals, fuzzy control charts used in sample case studies, and to extract key points of each paper in minimum time.

Fuzzy Control Chart Fuzzy Set Theory Literature Review Conceptual Classification
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IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2049 10.22034/2014.2.04 Research Paper An Integrated Inventory Model with Controllable Lead time and Setup Cost Reduction for Defective and Non-Defective Items An Integrated Inventory Model with Controllable Lead time and Setup Cost Reduction for Defective and Non-Defective Items Vijayashree M The Gandhigram Rural Institute – Deemed University, Gandhigram Uthayakumar R The Gandhigram Rural Institute – Deemed University, Gandhigram 01 08 2014 1 2 190 215 31 07 2014 13 11 2014 Copyright © 2014, Kharazmi University. 2014 http://www.ijsom.com/article_2049.html

In this paper, the study deals with the lead time and setup reduction problem in the vendor-purchaser integrated inventory model. The cost of capital (i.e., opportunity cost) is one of the key factors in making the inventory and investment decisions. Lead time is an important element in any inventory system. The proposed model is presents an integrated inventory model with controllable lead time with setup cost reduction for defective and non defective items under investment for quality improvement. In this analysis, the proposed model, we assumed that the setup cost and process quality is logarithmic function. Setup cost reduction for defective and non defective items, is the main focus for the proposed model. The objective of the proposed model is to minimize the total cost of both the vendor-purchaser. The mathematical model is derived to investigate the effects to the optimal decisions when investment strategies in setup cost reductions are adopted. This paper attempts to determine optimal order quantity, lead time, process quality and setup cost reduction for production system such that the total cost is minimized. A solution procedure is developed to find the optimal solution and numerical examples are presented to illustrate the results of the proposed models.

Integrated inventory model Vendor-purchaser coordination Lead time crashing cost Setup cost reduction for defective and non defective items
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A study of cooperative advertisings in a manufacturer-retailer supply chain, International Journal of Information and Management Sciences, Vol. 20, pp. 15-26. Woo, Y.Y., Hsu, S.L. and Wu, S.H. (2001). An integrated inventory model for a single vendor and multiple buyers with ordering cost reduction, International Journal of Production Economics, Vol. 73, pp. 203-215. Zhang, T., Liang, L., Yu, Y. and Yan, Y. (2007). An integrated vendor-managed inventory model for a two-echelon system with order cost reduction, International Journal of Production Economics, Vol. 109, pp. 241-253.
IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2048 10.22034/2014.2.05 Research Paper Inventory Model for Deteriorating Items with Four level System and Shortages Inventory Model for Deteriorating Items with Four level System and Shortages Tripathi Rakesh Prakash Graphic Era University, Dehradun (UK) India 01 08 2014 1 2 216 227 29 05 2014 13 11 2014 Copyright © 2014, Kharazmi University. 2014 http://www.ijsom.com/article_2048.html

This paper presents an inventory model for deteriorating items in which shortages are allowed. It is assumed that the production rate is proportional to the demand rate and greater than demand rate. The inventory model is developed by considering four different circumstances. The optimal of the problem is obtained with the help of Mathematica 7 software. Numerical examples are given to illustrate the model for different parameters. Sensitivity analysis of the model has been developed to examine the effect of changes in the values of the different parameters for optimal inventory policy. Truncated Taylor’s series is used for finding closed form optimal solution.

Inventory Constant demand Deterioration Shortages Production
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K., and Mishra, U. (2010). An inventory model for Weibull Time- dependent demand rate with completely backlogged shortages. International Mathematical Forum, Vol. 5(54). pp. 2675-2687. Urban, T.L.(2012). An extension of inventory models incorporating financing agreements with both suppliers and customers. Applied Mathematical Modelling, Vol. 36, pp. 6323-6330. Yang, H.L., Teng, J.T. and Chern, M.S. (2010). An inventory model under inflation for deteriorating items with stock- dependent consumption rate and partial backlogging shortages. International Journal of Production Economics, Vol. 123, pp. 8-19.
IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2101 10.22034/2014.2.06 Research Paper Presenting a Multi Objective Model for Supplier Selection in Order to Reduce Green House Gas Emission under Uncertion Demand Presenting a Multi Objective Model for Supplier Selection in Order to Reduce Green House Gas Emission under Uncertion Demand Mohamadi Habibollah Department of Industrial Engineering, Science & Research Branch, Islamic Azad University, Qazvin, Iran Sadeghi Ahmad Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran 01 08 2014 1 2 228 244 09 03 2014 07 12 2014 Copyright © 2014, Kharazmi University. 2014 http://www.ijsom.com/article_2101.html

Recently, much attention has been given to Stochastic demand due to uncertainty in the real -world. In the literature, decision-making models and suppliers' selection do not often consider inventory management as part of shopping problems. On the other hand, the environmental sustainability of a supply chain depends on the shopping strategy of the supply chain members. The supplier selection plays an important role in the green chain. In this paper, a multi-objective nonlinear integer programming model for selecting a set of supplier considering Stochastic demand is proposed. while the cost of purchasing include the total cost, holding and stock out costs, rejected units, units have been delivered sooner, and total green house gas emissions are minimized, while the obtained total score from the supplier assessment process is maximized. It is assumed, the purchaser provides the different products from the number predetermined supplier to a with Stochastic demand and the uniform probability distribution function. The product price depends on the order quantity for each product line is intended. Multi-objective models using known methods, such as Lp-metric has become an objective function and then uses genetic algorithms and simulated annealing meta-heuristic is solved.

Stochastic demand Greenhouse gas emission Genetic Algorithm Simulated Annealing L-p metric
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IJSOM Kharazmi University International Journal of Supply and Operations Management 23831359 Kharazmi University 2095 10.22034/2014.2.07 Research Paper A Novel Hierarchical Model to Locate Health Care Facilities with Fuzzy Demand Solved by Harmony Search Algorithm A Novel Hierarchical Model to Locate Health Care Facilities with Fuzzy Demand Solved by Harmony Search Algorithm Alinaghian Mehdi Department of Industrial and Systems Engineering, Isfahan University of Technology, 84156-83111 Isfahan, Iran Hejazi Seyed Reza Department of Industrial and Systems Engineering, Isfahan University of Technology, 84156-83111 Isfahan, Iran Bajoul Noushin Department of Industrial and Systems Engineering, Isfahan University of Technology, 84156-83111 Isfahan, Iran 01 08 2014 1 2 245 259 29 09 2014 05 12 2014 Copyright © 2014, Kharazmi University. 2014 http://www.ijsom.com/article_2095.html

In the field of health losses resulting from failure to establish the facilities in a suitable location and the required number, beyond the cost and quality of service will result in an increase in mortality and the spread of diseases. So the facility location models have special importance in this area. In this paper, a successively inclusive hierarchical model for location of health centers in term of the transfer of patients from a lower level to a higher level of health centers has been developed. Since determination the exact number of demand for health care in the future is difficult and in order to make the model close to the real conditions of demand uncertainty, a fuzzy programming model based on credibility theory is considered. To evaluate the proposed model, several numerical examples are solved in small size. In order to solve large scale problems, a meta-heuristic algorithm based on harmony search algorithm was developed in conjunction with the GAMS software which indicants the performance of the proposed algorithm.

Hierarchical Facility Location Successively Inclusive Fuzzy Credibility Theory Harmony Search Algorithm Health care facilities
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