PRODUCTION AND OPERATIONS MANAGEMENT
Year:2012 | Volume:2 | Issue:2 (3)|Papers Count:7

In this paper a novel mathematical model has been proposed for multi-objective scheduling problem in a cellular manufacturing system (CMS) with the aim of minimizing the maximum completion time of jobs (i.e., makespan or Cmax), the earliness cost and the tardiness cost. Due to the complexity of such a hard problem, a hybrid algorithm, based on a genetic algorithm (GA) and particle swarm optimization (PSO), has been proposed to solve the presented model in a reasonable computational time. Furthermore, non-dominated sorting genetic algorithm (NSGA-II) as a well-known multi-objective evolutionary algorithm has been used to analyze and highlight the efficiency of the proposed hybrid algorithm. The associated results of the algorithms have been compared and analyzed. Finally, conclusions have been made and suggestions for further study have been presented.

In progressing towards excellence, many barriers and problems appear which reveal the importance of self-assessment. One of the popular models of self-assessment is the excellence model of EFQM. In this study, the attitude of managers and personnel towards excellence criteria has been examined in order to measure the extent of excellence criteria governance. The main hypothesis of this research is: "there is a significant difference between the scores of current and desirable status of the excellence criteria in the company". This hypothesis has been separated into a number of sub-hypotheses. The statistical population of the research includes 157 respondents including managers, supervisors and staff of company out of which, 112 individuals have been selected randomly. All hypotheses except the second, the third, and the eighth (related to policy and strategy, resources and partners and society results) have been confirmed at 95% level of confidence. Furthermore, data analysis and research findings have revealed those areas which need improvement.

Six Sigma is one of the most popular systems for eliminating waste, reducing cost and improving quality in organizations. The process of evaluation and selection of projects is the first step towards implementing Six Sigma and many researchers believe that these are important for the success of such projects. Respectively, in this paper, a model has been proposed based on artificial neural network (ANN) as an effective tool for non-linear information processing. In this model, six criteria of project cost, project duration, number of Black and Green Belts, improving customer satisfaction, impact on business strategy and financial impact have been identified as input factors, and productivity and sigma level of improvement projects have been estimated using multi-layer perception (MLP). Finally, sensitivity analysis has been used for evaluation of the influence of inputs on outputs. The findings imply that 'business strategy' and 'financial impact' have the most and the least influence on model's outputs, including productivity and Sigma level, respectively.

Regarding mass investment in systems by organizations for capturing knowledge and improving intellectual capital which is not necessarily effective, evaluation of the success of knowledge innovation is underlined. The main contribution of this paper is proposing a novel approach for evaluating knowledge management systems (KMSs). The proposed approach is an integration of two well-established managerial methodologies of critical success factors (CSFs) and grey relational analysis. In the new approach, CSFs are used for defining KMS evaluation criteria and grey relational analysis is used to estimate the score of knowledge innovations and to prioritize them. Statistical population includes those firms in which, KM project is implemented. In the proposed approach, strategic coordination of KM and business, quality of KMSs, knowledge quality, user satisfaction, documents management, communications, top managers' support and culture are important factors in evaluating knowledge innovations in organizations. Applicability of the proposed approach has been addressed by analyzing data of five IT-based firms that utilized KMSs.

Profile monitoring is a new research subject in Statistical Process Control which has been recently considered by many researchers. Profile describes the relationship between a response variable and one or more independent variables. This relationship is often modeled using regression which can be simple linear, multiple linear, polynomial or sometimes nonlinear. To monitor polynomial profiles, some methods have been developed, the best of which is the orthogonal polynomial approach. One of the disadvantages of this method is the large number of control charts which are simultaneously used. In this paper, a new approach has been proposed based on orthogonal polynomial approach, in which only two control charts are used to monitor a kth-order polynomial profile. Simulation findings and average run length (ARL) curve analysis imply better performance of the proposed approach compared to the existing approach. Also, using the proposed approach is much easier in practice.

In this paper, a nonlinear model for locating service facilities is introduced in a competitive ‎region. In the proposed model the factors of travel time, quality of service facilities and price ‎are considered that are the most important effective factors in attracting and maintaining the ‎customers in the competitive environments. For identifying the customers’ probabilistic ‎behavior in selecting the competitor’s and entering firm’s facilities, the spatial interaction ‎model and Logit function are used. Since the decision making for locating is not only based on ‎the sale quantity and market demand captured and ignoring other important organizational ‎goals such as minimizing the cost may provide problems in long term for firms, therefore in ‎addition to the capturing demand, the fixed cost of locating is considered in the model that ‎will provide better results in the real world problems. Due to the computational complexity, a ‎genetic algorithm is developed for solving the model. The numerical results verify the ‎performance of the proposed model and effectiveness of‏ ‏‎ the genetic algorithm in solving it‏ ‏and show that the study of costumers’‎‏ ‏probabilistic demand considering the factors of price, ‎travel time and quality of service facilities has the major role in the increasing of sale and profit ‎of the entering firm, so that, in spite of selecting the most appropriate locations by the ‎competitor, the‏ ‏sale and profit quantities of entering firm are more than the competitor’s, in the ‎equal situation of price, quality and number of facilities.‎

Selection and appointment of best people in any job is an important decision. In this regard, management of the universities is one of the concerning subjects and respectively, head of departments are also important due to their influence on the performance of faculties. In this paper the quality of competency based selection and appointment of head of departments has been studied considering five dimensions of professional knowledge, intellectual and behavioral skills,  personality characteristics, attitude, insight and honor of people and the gap between present and desired status  has been analyzed according to the viewpoints of faculty members of Yazd University. The data has been collected through literature review, interview and questionnaire. The validity of designed questionnaire has been approved by a group of experts. 175 questionnaires have been distributed among faculty members of 30 departments of Yazd University in 2009, out of which, 122 have been completed and returned. The reliability of questionnaire has been computed using Cronbach's alpha as 0.97. The findings imply that at the current status, the dimensions of "personality characteristics" and "professional knowledge" are of most and least concern, respectively. The findings of calculating weighted negative gap in departments imply that less consideration of personality characteristics is the major reason for selection of incompetent head of departments. By ranking elements of this dimension using TOPSIS technique, it has been found that concentration on factors such as challenging, age, resistance against pressure, freshness and sociality and patience could further improve the current status. Therefore, with a proper planning for quality improvement of the elements of the mentioned dimensions, the probable problems and obstacles towards desirable performance of faculties can be rapidly removed.