نشریه مدیریت صنعتی
سال نهم شماره 25 (تابستان 1396)

The purpose of this paper is to explain the most appropriate approaches for traffic modeling in vehicle routing problem based on green transportation paradigm. There are four approaches in literature for modeling of traffic including: simple, discrete, continuous, and random. Based on the qualitative meta-analysis method, 67 sources of green transportation were examined descriptively (in terms of using the above-mentioned approaches based on descriptive statistics) and evaluating (assessing the strengths and weaknesses of the approaches), which resulted in It was better to use a continuous approach. Regarding the existence of different patterns of modeling in the continuous approach, in order to achieve the appropriate model, Zamzam's distribution network was used based on Tehran Pars sales data on 21 August 2016. The results showed that existing patterns were inappropriate and that a proper pattern for the Zamzam distribution network should be developed. The developed pattern consists of two indicators: 1) the definition of the virtual node; and 2) the calculation of the average speed, taking into account multiple traffic conditions. This pattern corrects the weaknesses of previous patterns based on continuous approach.

a lot of studies have been done about customer credit scoring, considering importance of the topic on credit institutions decision making. As an evolutionary computation method, Genetic algorithm is one of the methods used in this field. A variety of papers are published on comparing the performance of genetic algorithms with other scoring method but there is little information regard to fitness functions while these fitness functions play a vital role in overall performance of the model. To further investigation of the problem, three different fitness functions are proposed in the current paper and their performance is compared with other scoring methods including logistic regression and data envelopment analysis. The obtained results have shown that genetic algorithms quadratic function totally outperformed other methods based on accuracy, detection and sensitivity criteria.

The aim of this study is to identify factors influencing the commercialization of academic research achievements and to design its Structural Model. The research is applied and the method is mixed. The population in qualitative is experts, and in quantitative is faculty of engineering colleges in state universities in Tehran. The sample size in qualitative is 55 (purposive sampling) and in quantitative is 334 (stratified random). To collect data, semi-structured interviews and questionnaires were used. To validate the qualitative section, the member check and peer check and to reliability, method of agreement between the two coders was used. To validate quantitative section, content and construct validity and Cronbach's alpha coefficient was used to determine the reliability of the questionnaire. The findings are a conceptual model and identify independent variables in four categories: individual factors, internal, external, and academic gatekeepers. Goodness of fit index (GFI) was 0.88 and root mean square residual latent variables model was RMSEA = 0.072. The results indicate that the commercialization in universities as well as internal factors, lower than average level.

In this paper, the impact of productivity shocks on GDP using advanced algorithm approach and the Monte Carlo simulation in the Iranian economy has been surveyed. After reviewing the theoretical and experimental studies, the variables of inflation, unemployment, potential production and productivity shocks are selected as the variables explaining the variable of gross domestic product. Using three algorithms of fireflies, cuckoo, and particle swarms optimization, the coefficients of each of the independent variables were estimated. After estimating the coefficients and given the uncertainty of the estimated coefficients by the advanced algorithms, Monte Carlo method was used to simulate the equations. Comparing the findings obtained from the simulation and findings of the estimation indicate the high accuracy of the findings obtained from estimates. Given the obtained findings, productivity shocks had very little impact on GDP and the potential production was introduced as the most influential variable.

A nation’s progress and development depends on the production of knowledge by its educational centers and turning them into presentable products by the industrial units. To reach this point, a coherent connection between the scientific and industrial units in the country seems natural and inevitable. This research aims at scrutinizing the cooperation network between Hormozgan University and Industry. This study has an applied and practical nature and can be classified as a descriptive and survey-based research. The statistical population for the study includes Hormozgan University faculty members and managers of research centers in a number of Hormozgan organizations. In order to analyze this cooperative network, at first, two sets of questionnaires containing items for studying the network connections were designed. After completing the questionnaires, the data for each network was imported into Excel as a matrix and analyzed by using Visone and NetDraw applications and indexes such as the inner core angle, cutpoints and network densities were derived and computed for the networks. All in all, the cooperation and trust networks analysis indicated that the presented networks had a relatively low central density. The high points of isolation in two networks and the lower density of networks of trust compared to the cooperative networks indicate that the two parties have not been able to develop and establish a good level of satisfaction and trust in the intended cooperative paths and, consequently, it can be maintained that there is an almost weak level of communication and trust between Hormozgan University and business environments (i.e., industry) in these networks.

Passenger safety is one of the basic principles of traffic engineering and transportation planning, so that in developed countries, along with the development of other traffic engineering sections, attention is being paid and, by conducting studies and analyzes, attempts are made to crash and resultant consequences Minimize it. The present research studies the application of data mining in identifying incident points. The study area is 15 km from the Haraz road. The collected data from the police information technology unit of Navarra was analyzed using SPSS Modeler software using data mining method. The results show that the three points of the Goznak, the Wana and Shanglunn tunnels are part of the accidental areas in this area. In order to reduce accidents in this axis, it is suggested that the geometric modification of the accidental points, as well as the dual-tracking of the road and the consideration of lightning, be put on the agenda of the relevant organizations.

Nowadays expert systems are used as one of the most useful and most practical decision support systems. These systems are relying on knowledge of experts in certain domain combines valuable experience with speed and accuracy of computer and improve the quality of their judgments. One of the most extensive applications of these systems is medical diagnostic fields. Different from what happened in most prior researches in the development of expert systems, in the present study using the situational logic in the process of knowledge acquisition and fuzzy inference engine architecture approach is recommended. Identify the type of epilepsy has always been one of the most challenging deliberations among the neurologist doctors and strict distinction between the types of the disease, according to the closely signs Creates conflict among the field's doctors that the expert system is able to solve this problem with the accuracy of 83 percent. Forming a comprehensive knowledge base using analysis of competing hypotheses (ACH) modeling in order to distinguish between 14 types of epilepsy disease is the distinctive features of this study. Research done on the project can be used to diagnose other diseases that have similar symptoms closely and to be pragmatic. The proposed system can be used in situations where access to neurologist doctors is impossible can be very useful.

Inventory routing problem considers inventory allocation and routing problems simultaneously, in which the replenishment policies and routing arrangement are determined by the supplier under the vendor managed inventory mode. In this paper we study deterministic inventory routing problem in a pharmaceutical supply chain with a distributor and multiple geographically dispersed retailers. Two types of products are considered, first refrigerated which need temperature-controlled vehicles to be delivered and second non-refrigerated. Therefor our problem is defined in a cold chain which is a temperature-controlled supply chain. Vehicles capacity and holding capacity of retailers is consist of refrigerated and non-refrigerated parts. We propose a mixed integer linear programming (MILP) model. The objective is to minimize the sum of transportation and inventory costs. We also propose an adaptive large neighborhood search heuristic to solve the problem. In the initialization phase of the algorithm, a two phase heuristic algorithm is proposed. We used standard data sets to demonstrate the performance of the proposed algorithm.