PRODUCTION AND OPERATIONS MANAGEMENT
Year:2011 | Volume:2 | Issue:1 (2)|Papers Count:7

In this paper a multi-commodity multi-period inventory routing problem in a two-echelon supply chain consisting of a manufacturer and a set of retailers has been studied. In addition to inventory management and distribution planning, production planning has also been considered in the above problem. The objective is to minimize total system cost that consists of production setup, inventory holding and distribution costs. The commodities are delivered to the retailers by an identical fleet of limited capacity vehicles through direct shipment strategy. Also it is assumed that production and storage capacity is limited and stockout is not allowed. Since similar problems without distribution planning are known as NP-hard, this is also an NP-hard problem. Therefore, in this paper, a new improved particle swarm optimization algorithm has been developed consisting of two distinguished phases for problem solving. First, the values of binary variables are determined using the proposed algorithm and then, the continuous variables are calculated by solving a linear programming model. Performance of the proposed algorithm has been compared with genetic and original particle swarm optimization algorithms using various samples of random problems. The findings imply significant performance of the proposed algorithm.

In the world of today, most of countries attempt to improve their productivity and economic status by concentrating on innovation. Organizations have considered factors affecting innovation and have achieved enormous competitive advantages. The aim of this research is to investigate the influence of organizational climate in terms of seven dimensions of cohesiveness, autonomy, challenge, resources, openness to innovation, encouragement and supervision on process innovativeness. Data has been collected by random sampling in Khodro car Lizing company as a subdivision of Iran Khodro Industrial Group. The validity of the conceptual models of each dimension of climate and process innovativeness has been assessed by confirmatory factor analysis (CFA). Results imply the validity of causal relationship between components and the latent variable except for the cohesiveness dimension. Finally, the hypotheses of research have been examined by structural equation modeling (SEM). Findings imply that challenge, resources, openness to innovation, and supervision influence process innovativeness. Supervision has the highest influence and openness to innovation has negative influence on innovativeness, while in prioritizing the factors by the Vikor technique, openness to innovation has the first rank.

Data envelopment analysis (DEA) is known as one of the most common approaches for efficiency evaluation. Network models are new subjects in which, a DMU with all its subunits and links is considered as a network structure. One of the most widely used DEA methods for network data is the suggested approach of Lewis and Sexton. In this approach, performance of each DMU is measured compared to a similar DMU by moving on the effective paths and then computing the final outputs and classic primary inputs. In reality, many cases can be found that an original input or an intermediate product allocates to several subunits or forms a tour in a network. In such networks, the approach of Lewis and Sexton is not able to calculate efficiency. Therefore, in this paper, an approach has been proposed for solving such problems and computing the efficiency of such networks.

Due to continuous changes in organizational environment, there is no warranty for long term survival in the market. Currently, those organizations can succeed that are agile and able to rapidly respond to environmental requirements. In this research a model has been proposed for applying proper strategies for achieving long term organizational success. The proposed model is an integration of Balanced Score Card (BSC) approach, Fuzzy Quality Function Development (FQFD) and Zero-One Goal Programming (ZOGP). In fact by BSC, appropriate strategic plans can be designed and prioritized by FQFD. Then, based on multiple objectives and existing problem constraints, feasible strategic plans are identified by ZOGP. Findings imply that decision making techniques can be well utilized in designing BSC through a structured methodology, make improvement in all aspects and have a positive influence on organization's performance in long term.

The main purpose of this research is to address how robust design of service quality dimensions can be obtained. Designing service quality system by robust design can result in determination of optimum levels of service quality dimensions. Literature review indicates that studies have been mostly concentrated on determination of service quality dimensions and their relationship with customer satisfaction. In this investigation, service quality robust design has been conducted by the integration of Taguchi design of experiments and SERVQUAL approach in Iran Travel Agency. For this purpose, five basic dimensions of service quality, i.e. reliability, responsiveness, assurance, empathy, tangibles and price have been assumed as control factors. Response factor has been defined as two alternatives of the sum of customer expectations and the sum of service quality gaps. Noise factor has not been considered in this study. The advantage of this approach compared to classic approaches of design of experiments is the simultaneous improvement of mean value and standard variation. Signal to noise ratio (S/N) has been computed and the desired mix of the levels of service quality dimensions has been determined, respectively. Comparing the two sets of findings can assist the agency in analyzing the cost of attracting new customers and retaining regular customers.

In the competitive world of today, organizations should strictly attempt and utilize appropriate strategies towards survival and growth. Environment of organizations and customer demands are rapidly changing. Another critical subject is the limitation of resources and facilities. Appropriate selection and ranking of agile suppliers and outsources are effective ways for solving such problems. This study is a result of two master theses of the second and third authors in the agility and Interpretive Structural Modeling (ISM) subjects. In this research, the indicators of agile suppliers have been initially determined and leveled by the ISM approach. An integrative approach of Analytic Hierarchy Process (AHP) and Fuzzy TOPSIS method has been proposed to determine final ranking. In fact, in order to improve the efficiency of the results of Fuzzy-TOPSIS method, the weights have been determined by the Analytic Hierarchy Process (AHP) and in order to interpret the influence of indicators on the agility of suppliers, the ISM approach has been used simultaneously. The findings imply that the indicator of delivery speed is placed at the first level output of the model and has an appropriate acceleration. Also, the indicator of delay time reduction has the same advantage. By the use of Fuzzy AHP, the weights of suppliers' agility have been determined and considered as entering data to the TOPSIS model. Finally, six suppliers have been ranked by the Fuzzy TOPSIS method. The calculations have been attached as an Excel file. The findings also imply that those indicators that have higher acceleration and less dependency have higher weights in the AHP model, therefore, the variables of first and second levels of ISM should be more concentrated in order to improve suppliers' agility.

The aim of this paper is to estimate the parameters of Binary Logistic Regression model for maximizing the log-likelihood function with improved association indicators. Logistic regression, similar to other parameter estimation approaches, requires an indicator for the estimation appropriateness of its parameters, one of which is the association indicator. The association indicators demonstrate the frequency of success responses occurred against failure in certain number of Bernoulli independent experiments. In parameter estimation, existing indicators' values are not sensitive to the parameter values, whereas the proposed indicators are sensitive to the estimated parameters during the iterative procedure. Therefore, the innovation of this study is in proposing a new association indicator of Binary Logistic Regression with more sensitivity to the estimated parameters in maximizing the log-likelihood in iterative procedure. Findings of an example analysis and their comparison with association indicators imply higher accuracy and appropriateness of the proposed indicators.