Modelling the Level of Adoption of Analytical Tools; An Implementation of Multi-Criteria Evidential Reasoning Igor Barahona Chapingo Autonomous University (UACh) , Carretera México, Texcoco de Mora, MEX, Mexico author Judith Cavazos Popular Autonomous University of Puebla State. Puebla, Mexico author Jian-Bo Yang Manchester Business School (MBS) author text article 2014 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 1 v. 2 no. 2014 129 151 http://www.ijsom.com/article_2104_8f4feb0ad908cf0884aa4574d7960f3d.pdf dx.doi.org/10.22034/2014.2.01 The Variance-covariance Method using IOWGA Operator for Tourism Forecast Combination Liangping Wu College of Mathematics and Software Science, Sichuan Normal University, Chengdu, China. author Jian Zhang Visual Computing and Virtual Reality Key Laboratory of Sichuan Province, Sichuan Normal University, Chengdu, China. author text article 2014 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 1 v. 2 no. 2014 152 166 http://www.ijsom.com/article_2047_208dd2545c4d51ba0c632f9f94b9dad4.pdf dx.doi.org/10.22034/2014.2.02 A Literature Review on the Fuzzy Control Chart; Classifications & Analysis Mohammad Hossein Zavvar Sabegh Kharazmi University, Tehran, Iran author Ablofazl Mirzazadeh Kharazmi University, Tehran, Iran author Saber Salehian Kharazmi University, Tehran, Iran author Gerhard Wilhelm Weber Middle East Technical University,Ankara, Turkey author text article 2014 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 1 v. 2 no. 2014 167 189 http://www.ijsom.com/article_2046_f66cf3d0a52ee7650756e8627102de9e.pdf dx.doi.org/10.22034/2014.2.03 An Integrated Inventory Model with Controllable Lead time and Setup Cost Reduction for Defective and Non-Defective Items M Vijayashree The Gandhigram Rural Institute – Deemed University, Gandhigram author R Uthayakumar The Gandhigram Rural Institute – Deemed University, Gandhigram author text article 2014 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 1 v. 2 no. 2014 190 215 http://www.ijsom.com/article_2049_891c6f2afe3deec3837198bbadf14cb9.pdf dx.doi.org/10.22034/2014.2.04 Inventory Model for Deteriorating Items with Four level System and Shortages Rakesh Prakash Tripathi Graphic Era University, Dehradun (UK) India author text article 2014 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 1 v. 2 no. 2014 216 227 http://www.ijsom.com/article_2048_23744adecf6428f88d10639e6e328f18.pdf dx.doi.org/10.22034/2014.2.05 Presenting a Multi Objective Model for Supplier Selection in Order to Reduce Green House Gas Emission under Uncertion Demand Habibollah Mohamadi Department of Industrial Engineering, Science & Research Branch, Islamic Azad University, Qazvin, Iran author Ahmad Sadeghi Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran author text article 2014 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 1 v. 2 no. 2014 228 244 http://www.ijsom.com/article_2101_bbd89d62b2d952d77c1174a07d078ab6.pdf dx.doi.org/10.22034/2014.2.06 A Novel Hierarchical Model to Locate Health Care Facilities with Fuzzy Demand Solved by Harmony Search Algorithm Mehdi Alinaghian Department of Industrial and Systems Engineering, Isfahan University of Technology, 84156-83111 Isfahan, Iran author Seyed Reza Hejazi Department of Industrial and Systems Engineering, Isfahan University of Technology, 84156-83111 Isfahan, Iran author Noushin Bajoul Department of Industrial and Systems Engineering, Isfahan University of Technology, 84156-83111 Isfahan, Iran author text article 2014 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 1 v. 2 no. 2014 245 259 http://www.ijsom.com/article_2095_479cc1590767a060545ee5b5b42d803c.pdf dx.doi.org/10.22034/2014.2.07