This paper presents an empirical investigation to identify and rank the factors of information market development systems influencing on the market share development. The population of this survey includes all managers who work for SMEs in city of Tehran, Iran. The study selects a sample of 230 people randomly and a questionnaire is distributed among them in Likert scale. Cronbach alpha has been calculated as 0.814, which is well above the minimum desirable level. Using structural equation modeling the study has determined seven factors including valid data, information, strategic information, organizational information, supportive information, customer information, development information and data analysis, which influence market share development.

This work deals with production scheduling problem in an assembly flow shop, having parts machining followed by their subsequent assembly operations. Limited heuristics available on the problem, are based on unrealistic assumption that every part is processed on all machines. In this paper, two heuristics NEH_BB and Disjunctive are proposed to solve assembly flow shop scheduling problem where every part may not be processed on each machine. Exhaustive computational experiments are conducted with 60 trials each. The methods are found to be applicable to large size problems. The objective functions used for comparison are makespan and computational time. Disjunctive method takes very less computational time as compared to NEH_BB and hence claimed to be the better among available approaches for finding solution in assembly flow shop problems.

An innovative price plan monitoring and advisory system simulates subscriber usage consumption for offering suitable price plan. The aim of this paper is to develop the decision support system by using Statistical Process Control (SPC) to identify subscriber usage behavior and provide critical visibility into subscriber consumption to detect their inappropriate usage especially in exceeding usage. To explore subscriber usage behavior, a forecasting model and a regression is employed to identify related factors and predictive usage model. The innovative price plan monitoring and advisory system has been verified and validated with one of the largest telecommunication company in Thailand. Using decision support system with effective control chart and real subscriber behavior pattern help mobile network operator grow their revenues and profits by offering an appropriate price plan as well as improve subscriber experience with more flexible choice to meet their individual usage consumption needs.

Enterprise Resource Planning System is an important investment for organizations and determines future competitiveness and performance of a firm, which could be substantially effective. The primary objective of enterprise resource planning systems is to consolidate operational procedures among various departments, management information systems and resource allocation of the companies. Given the fact that the selection process for enterprise resource planning system is a multi-criteria decision problem and there are some ambiguities with various criteria, the use of fuzzy logic is inevitable, therefore, in this study, the main indices and standardized evaluation software enterprise resource planning system identification were used to rank six software packages including Oracle, SAP, SSA Global Solution, Sage Group, Microsoft Business Solution, People Soft focus. The results indicate that the highest priority is associated with the SAP software.

In decision making when multiple criteria are determined, the best choice depends on having complete information and proper decision-making technique. The permutation method is one of the popular techniques used in the context of multiple criteria decision making (MCDM). In this paper, a method is presented where there is more than one vector of weights for the criteria and there are uncertainties associated with criteria weights or there are multiple decision makers. We first take different weight vectors to create a multi-objective problem and then we solve them simultaneously to achieve appropriate Pareto solutions of the permutation method. Therefore, MOPSO and NSGA-II algorithms are utilized to find non-dominated solutions. Some examples in different sizes are considered to compare the efficiency of the proposed methods. Results show that by increasing the number of options and considering the computational time, the proposed methods perform better compared with the exact method. Moreover, NSGA-II is more efficient than MOPSO for the considered problem.

Control chart pattern (CCP) recognition can act as a problem identification tool in any manufacturing organization. Feature-based rules in the form of decision trees have become quite popular in recent years for CCP recognition. This is because the practitioners can clearly understand how a particular pattern has been identified by the use of relevant shape features. Moreover, since the extracted features represent the main characteristics of the original data in a condensed form, it can also facilitate efficient pattern recognition. The reported feature-based decision trees can recognize eight types of CCPs using extracted values of seven shape features. In this paper, a different set of seven most useful features is presented that can recognize nine main CCPs, including mixture pattern. Based on these features, decision trees are developed using CART (classification and regression tree) and QUEST (quick unbiased efficient statistical tree) algorithms. The relative performance of the CART and QUEST-based decision trees are extensively studied using simulated pattern data. The results show that the CART-based decision trees result in better recognition performance but lesser consistency, whereas, the QUEST-based decision trees give better consistency but lesser recognition performance.

An integrated information system based DSS is developed for Open and Distance Learning (ODL) institutions in India. The system has been web structured with the most suitable newly developed modules. A DSS model has been developed for solving semi-structured and unstructured problems including decision making with regard to various programmes and activities operating in the ODLIs. The DSS model designed for problem solving is generally based on quantitative formulas, whereas for problems involving imprecision and uncertainty, a fuzzy theory based DSS is employed. The computer operated system thus developed would help the ODLI management to quickly identify programmes and activities that require immediate attention. It shall also provide guidance for obtaining the most appropriate managerial decisions without any loss of time. As a result, the various subsystems operating in the ODLI are able to administer its activities more efficiently and effectively to enhance the overall performance of the concerned ODL institution to a new level.

Decision making problem is the process of finding the best option out of all feasible alternatives. There are some methods for solving Multiple Criteria Decision-Making problems and Simple Additive Weighting (SAW) is one of the most popular ones. In this paper, among multi-criteria models in making complex decisions and multiple attribute models for the most preferable choice, SAW technique is extended using interval numbers. For this purpose, we first propose a method for extending Entropy method for dealing with interval data, and then the extended SAW method with interval data is proposed by using the interval weights derived by the proposed interval Entropy method. The extended SAW method is an algorithm to determine the most preferable choice out of all possible choices, when the input data are stated in interval.

In this paper, a new multi-item inventory system is considered with random demand and random lead time including working capital and space constraints with three decision variables: order quantity, safety factor and backorder rate. The demand rate during lead time is stochastic with unknown distribution function and known mean and variance. Random constraints are transformed to crisp constraints with using the chance-constrained method. The Minimax distribution free procedure has been used to lead proposed model to the optimal solution. The shortage is allowed and the backlogging rate is dependent on the expected shortage quantity at the end of cycle. Two numerical examples are presented to illustrate the proposed solution method.

It is necessary for companies and industries to select the most appropriate maintenance strategy to increase the reliability and safety level with reasonable cost. The primary objective of this paper is to assess different maintenance strategies and to select the best and the most appropriate alternatives for Saipa vehicle industry in Tehran, Iran. For this purpose, we simultaneously consider numerous conflicting objectives and constraints. In this study to counter with this conflicting and to consider the dependency among the qualitative and quantitative criteria and sub-criteria, an integration of Analytic Network Process (ANP) and fuzzy set theory are considered. Therefore, factors playing important role in selecting the best maintenance strategy are determined by reviewing the research literature and interviewing with the experts by Delphi technique. Considering the relations among different factors, a network with 4 criteria and 28 sub-criteria are proposed. In the next step, ANP technique is applied for ranking effective factors in evolution of appropriate maintenance strategy. Results reveal that the best maintenance strategy for fixture body of pride (setter) is corrective maintenance.