فهرست مطالب محمدعلی بهشتی نیا

Today, the use of multi-site manufacturing systems has attracted the attention of many factories due to its benefits, such as reduced transportation costs, concentration of population, pollution, facilities and traffic in one area, and improved service to customers. This paper addresses the problem of scheduling a distributed flexible job-shop scheduling problem with two objective functions of minimizing the total delivery times of orders and the total production and transportation costs. In this case, it is assumed that there are several manufacturing units in different geographic regions, each of which has a flexible job-shop environment. The purpose of this paper is to determine how to allocate orders to manufacturing units, assign operations to machines of the related manufacturing unit, and determine sequence of processing of the assigned operations to a machine for minimizing the total delivery times of orders and the total production and transportation costs. Since the problem has NP-Hard complexity, meta-heuristic algorithms should be used solve it. In this paper, a genetic algorithm is proposed to solve the problem called a Bi-Gender genetic algorithm with two sets of chromosomes. The first group of chromosomes is male and the second group of chromosomes is female. In order to perform a crossover operator, one parent should be selected from the first category and the second one from the second category. Comparing the results of this algorithm with the development of a genetic algorithm in the subject literature indicates the high efficiency of the proposed algorithm.

The drug supply chain is a part of the health care system, which is of great importance in increasing the health of the community and therefore it is a critical issue in any country. In this paper, we have tried to deal with one of the most important challenges of the current pharmaceutical industry, namely the lack of coordination between different sectors of the chain, by presenting a mathematical model for integrated production-inventory-routing problem. The problem has two objective functions; the first objective function minimizes the total cost of the system, including fixed and variable costs of production, transportation, inventory and spoilage cost, and the second objective function minimizes environmental impacts caused by the production and transportation of drugs. In addition, in this paper, the production mode by several different manufacturers and two-stage distribution is considered. After presenting the mathematical model of the above problem, in order to cope with demand uncertainty, a scenario-based stochastic programming is used for modeling. The model will be implemented at BayerPool Pharmaceutical Company and the results will be analyzed. The results showed that increasing demand led to increases in both objective functions of the problem. At the end, sensitivity analysis is also done on two parameters of the problem. Increasing setup costs of production increases the total cost objective function and reduces the greenhouse gas emissions objective function.

One of the problems of service unit managers is identifying actions and prioritizing them to improve service quality. The purpose of this study was to determine combining Quality House method and SERVQUAL analysis in quality of medical clinic services.

This is a descriptive study. In this study, two statistical populations including Clinical Reference Society and Medical-Cosmetic Experts were used. From the first population, using Cochran formula with 5% error, 386 clients were randomly selected to complete "Importance Degree Questionnaire" and "SERVQUAL Questionnaire". In the second population, a sample of 4 physicians and 4 university teachers was selected to complete the “Relationship Matrix Questionnaire’. According to the validity of previous studies, their reliability was measured by Cronbach's alpha. At first, the clients 'demands for the clinic service were identified using the clients' comments and then their importance was calculated by the questionnaire of importance and difference between the current quality level and the expected quality level of the clients (quality gap) by the “SERVQUAL Questionnaire”. After determining the weight of each request, corrective measures were identified to meet these demands, according to the expert's opinion. Then, with the "Communication Matrix Questionnaire", the relationships of these corrective actions with the demands were determined and finally the weight of each corrective action was determined. Data were analyzed by SPSS. 16.

12 client requests and 15 corrective actions were identified and prioritized. "Physician performance" and "hygiene" were the most important demands and "Para clinical services" had the highest quality gap and the highest weight. Corrective measures of "skilled personnel recruitment" and "use of new medical equipment" were also top priorities.

Using a combination of quality house methodology and SERVQUAL analysis, corrective actions were identified to improve the quality of medical clinic services and prioritize their implementation. It is recommended to combine these two methods in determining corrective actions and prioritizing their implementation to improve the quality of medical clinic services.

This paper concentrates on the minimization of total tardiness and earliness of orders in an integrated production and transportation scheduling problem in a two-stage supply chain. Moreover, several constraints are also considered, including time windows due dates, and suppliers and vehicles availability times. After presenting the mathematical model of the problem, a developed version of GA called Time Travel to History (TTH) algorithm, inspired from the idea of traveling through history, is proposed to solve the problem. In order to validate the performance of the proposed algorithm, the results of TTH algorithm are compared with two other genetic algorithms in the literature. The comparison results show the better performance of the proposed algorithm. Moreover, the results of implementing the sensitivity analysis to the main parameters of the algorithm show the behavior of the objective functions when the parameters are changed.

Transportation and communication are considered as one of the fundamental issues in economy. These phenomena are seen as one of the indicators of development of countries. Nowadays, traffic accidents have become one of the main issues in transportation as well as the economy in developing countries. Roads, human errors, vehicles and environment have important roles in occurrence of accidents. Modification or elimination of hazardous spots known as black spots have considerable influence on safety promotion, traffic reduction, accidents, losses, and waste reduction. Prioritization Methods could improve the black spots; mostly based on single criteria methods. In this paper, a new approach to rank the black spots in various roads is proposed using natural and environmental criteria. The roads of Sabzevar to Neishaboor and vice versa are studied as a real case to implement the proposed approach. Firstly the criteria are identified using literature review and experts' opinions and the weight of each qualitative and quantitative criteria is calculated by modified digital logic (MDL) method. Afterwards, 7 black spots are identified according to the statements of the ministry of roads and the required data are collected. Finally, the prioritization of mentioned black spots is conducted using group TOPSIS approach. As one of the contributions of this paper to the literature is the presentation of a set of comprehensive criteria consisting of 4 main criteria and 18 sub-criteria to evaluate black spots of which 4 sub criteria are proposed by this research. Furthermore, in this paper a combination of MDL and group TOPSIS is used to rank black spots which is a new approach in this area.
Results demonstrate that the three factors number fatal accidents, maximum speed limit, and number of injury accidents are the most important factors, respectively. Also, Zaferanie residential area has the highest importance among black spots.

The world economy is increasingly characterized as a service economy. This is primarily due to the increasing importance and share of the service sector in the economies of most developed and developing countries. In fact, the growth of the service sector has long been considered as an indicator of a country's economic progress. The hospitality industry is a broad category of elds within the service industry that due to its fundamental in uence on national economy is one of the most sensitive elds to the matter of quality. Therefore, application of methods such as House Of Quality (HOQ) can be a big step forward in maximizing the customer satisfaction. Initially we investigated 31 essential customers' expectations from services of Rasht Pardis Hotel and then we prioritized these needs and carried out the Servqual and Kano analysis by sending out corresponding questionnaires to 390 customers. Afterwards, by means of house of quality, the proper acts and corrective actions to meet customers' needs is determined and prioritized. All this survey is done under rectangular fuzzy environment. The results acquired from this research can determine the priority of needs and correction actions, classify customer preferences to meet the customers' expectation at the highest possible. Results demonstrate that most important demands are respectively secure rooms, tidy and clean beds and blankets and well-designed Cafas and restaurants. Furthermore, entertainment facility for kids and 24*7 exchange centers and medical services have respectively the biggest gap to the desired conditions. Kano analysis show that 31 customers' expectations, 4 are must-be, 22 are attractive and the other 4 are one-dimensional qualities. Also, Activities Hiring well trained sta, hiring skilled technicians, Mechanization of dishwashing, cloths washing and etc., Codi cation of health and sanitary principles to insure quality and Creating website for online services such as reservation are the activities that have the highest importance level.

This paper aims to examine the scheduling of vehicles in a multi-product supply chain regarding to the mutual relationship between the transportation and the manufacturing units. The integration level in the supply chain consists of a manufacturer and its first tier suppliers, which are linked by a transportation fleet. The problem is determining orders allocation to the suppliers, orders production sequence at the suppliers, orders allocation to the vehicles, and orders transportation priority, in order to minimize the sum of orders delivery time. This issue has not been discussed in the literature, so far. At first, the mathematical model of the problem is presented, then the NP-Hardness of the problem is demonstrated. For solving the problem, a new combination of genetic algorithm and simulated annealing algorithm, named as Populated Simulated Annealing algorithm (PSA) is proposed. For verifying the PSA, its results are compared to results of simulated annealing algorithm (SA) and developed version of DGA algorithm, proposed for the nearest problem in the literature to our problem. Furthermore, relaxing some hypothesis, the results of PSA are compared to DGA results. All of the comparisons show that PSA is more efficient than the other algorithms. Finally, comparison of PSA with exact solution for small size problems demonstrates its proper efficiency.

Some of the important factors in the growth of developed countries include their management, beliefs and values that have shaped people's behavioral motivations. Management is an executive- social science that, in order to become operational, needs to be accepted by people. After identifying the elements of the principles of management, that are adaptable with the Islamic culture, this research prioritizes their implementation using Analytical Hierarchy Process Method (AHP) at a level of Islamic culture, which is influenced by the characteristics of Iran. Establishing a framework for adapting these principles to the people's culture will increase their executive guarantee. The results of the prioritization of management patterns in Iran are as follow: 1. if you make a mistake, do not worry about the problem, and just put it right at once, 2. do not ask why a job is not done yet; instead, think how you can do it and 3. match the products or services completely with the needs of the customers.

One of the main reasons for lack of competitiveness in automotive production in our country is mismanagement in supply of primary parts and transporting them to the domestic auto companies. This paper presents an integrated approach in order to make decisions to schedule orders of production and transportation, including assigning orders to suppliers and vehicles, sequencing production orders for suppliers and the way they are transported to Iran Khodro company. A shared transportation navigation is also considered in the problem. In order to optimize decisions in the proposed model, a genetic algorithm is used. In comparison to integrated and non-integrated models and the developed genetic algorithms used recently in the literature, the algorithm suggested in this paper gives a better performance. Furthermore, when compared to a real case, the proposed algorithm in this paper showed superior results.

Recently, Quality Function Deployment (QFD) is used as a systematic approach to establish an appropriate connection between customers’ needs and technical requirements of provided services by many companies. In this paper a hybrid model composed of QFD, Analytic Hierarchy Process (AHP) and knapsack problem using fuzzy approach is proposed to create this connection. Afterwards, a case study on police services is presented. Accordingly, customers’ needs from police services are detected and after determination of their importance level with fuzzy group AHP approach, they are positioned in rows of House Of Quality (HOQ) matrix. Also, the main police processes are placed in columns of HOQ matrix. Finally, a model based on knapsack problem model is proposed to determine the priory of executive activities for quality enhancement in police services, regarding budget constraint.

Introduction A hazard is a situation that poses a level of threat to life, health, property, or environment. Most hazards are dormant or potential, with only a theoretical risk of harm; however, once a hazard becomes "active", it can create an emergency. Preventing harmful results of natural disasters such as flood, earthquake, tsunami, storm and etc requires crisis management planning. One of the most important parts of fatality during this events is caused by weakness in transportation system, especially in injured transfer system to vital treatment. This paper proposes an injured transportation system which is one of the most important subjects in decreasing human fatality during crisis. In this system at first, casualties must be taken to a primary medical center by road relay vehicles (like ambulances, or personal vehicles), then be transferred to master medical centers by air relay vehicles (like helicopters) considering required treatment. On the other hand, due to the high price and limitation of air transportation, it is supposed that casualties will be transferred using integrated mode to the master medical centers. The most important reason of using air transportation is that when the natural disasters happen, roads are usually blocked as result of damages caused by crisis effects. Consequently, we have heavy traffic or blocking on the streets, highways and roads. Additionally, in proposed system every primary medical center can use common vehicles instead of independent transportation to move injures.
Importance of this subject is that it is possible to transfer wounded who are located in the same geographic area by using integrated transportation due to high damaging probability in foundations and usual paths when natural evens occur. Fast integrated transportation is considered in second stage. Finally, we compare our proposed transportation system with two other systems in which the first system uses direct transportation of injuries to the master medical centers and the second one uses two-stage transportation system by road vehicles. The aim is determining the assignment of injures to the air relay vehicles and determining the priority of injures for transferring to the master medical centers. The objective is minimizing the total waiting time of injures to receive to the master medical centers.
- Methodology This research is applicable and is done with analytical approach. To find the best parameters for alternatives of problems that are solved in this paper, we considered to 8 crisis engagement specialists and emergency section of master hospitals. Then to maximum coverage of problem ranges, 216 random problems are produced to consider several condition of problems in crisis. A genetic algorithm with variable chromosomes structure is proposed to solve and optimize these problems. In the field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a met heuristic) is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.
After codding the proposed algorithm, this problem is ran on several random problems. Structure of this random problems includes the various range of problems. All of the computational programs are written on Matlab R2013a and ran by a computer with Intel, corei5, 2.6GHz Processor.
After several runs and by experimenting, we understand that amounts 100 for populations, 0.05 for mutation rate, 0.5 for best parameter, and 50 for termination parameter, result to the best answers in a reasonable solving-time.
- Result and discussionThree scenarios have been proposed to survey in this problem, including: direct transfer of injuries to the master medical centers, integrated two-stage transfer by road vehicles and integrated two-stage transfer by a combination of road vehicles (in the first stage) and air vehicles (in the second stage),. All three scenarios are compared with each other. For this, 216 random test problems with different structures to have maximum coverage of crisis conditions is created and they have been solved by proposed genetic algorithm. Considering destruction of urban infrastructures when a disaster occurs, we considered a fast-air-transportation in part 2 of transportation system to deliver injures to master hospitals. Results is shown that the third scenario is the best injured transportation system scenario to minimize waiting injured time arriving to the master hospital (considering her sore). The numerical results represents this matter that using the system that is proposed in this paper have the less amount of waiting times comparison to 2 other scenarios that studied.
- ConclusionOne of the most effective issues on number of fatality resulted by natural disasters, is transportation systems to convey wounded to medical centers. In this essay we tried to survey ways of reducing waiting time of casualties to master medical centers using integrated transportation system and two-stage transfer. After problem representation a genetic algorithm to solve this problem is proposed. To survey results, we created several random problems in special structure that they show various range of problems. Then these random problems were solved by proposed algorithm. According to obtained numerical results, the proposed system have considerable effects on reduction of injures waiting time to master medical centers. Hence, it propose that stables a central data receiver-distributer organization to receive injures data from primary medical centers and transportation system condition, combine and solve them in proposed model and give transportation missions to system to minimize injures waiting time and saving more lives.
At the end, usage of integrated air transportation system may impose more expenses to system, but it has advantages like less injures waiting time to arrive to master medical centers, more reliability, less number of round trip, less number of vehicle and…, that can justify this expensiveness.

This paper studies a model for integration of vehicle routing problem (VRP) in a supply chain with order assignment to the suppliers and determining their production sequence. The considered supply chain consists of some suppliers, vehicles and a manufacturer. It is assumed that manufacturer purchases identify the raw material demand of suppliers in wholesale all at once. This provides the opportunity of receiving discounts and consequently decreasing final price. A transportation fleet composed of some vehicles, each of which may have a different speed and different transport capacity, is responsible for transporting purchased raw materials to suppliers and gathering completed parts from them aiming at minimizing the total tardiness of all jobs. After presenting the mathematical model of the problem, a dynamic genetic algorithm with two dimensional structures is proposed. The algorithm was applied to the supply chain of a medical equipment manufacturer and the results were compared with real results beforehand. Findings show that applying dynamic genetic algorithm results in improving the average of tardiness from 9.44 days to 2.11 days. Also the comparison of dynamic genetic algorithm with the optimum solution for the small size problems, and the algorithm proposed for the nearest problem in the literature to our problem shows the high efficiency of dynamic genetic algorithm.

Improving the quality of services in hospitals and dealing with the health of people are very important. The aim of the present study is to evaluate and rank the quality of service in four public hospitals in Iran through “Multi-criteria Decision Making Methods” in 2016.
In this descriptive study, a sample of 8 faculty members from both Semnan University and Isfahan University of Medical Science and a random sample of 384 patients from four public hospitals in Isfahan are calculated by using Cochran method with 0.05 error. Two “Pairwise Comparison Questionnaire” and “Decision Matrix Questionnaire” are used to weight the identified criteria and determine the score of each hospital in each criterion, respectively. Cronbach's alpha of the first questionnaire is approved by 10 experts and the second questionnaire by patients. The hospitals are ranked, using two combined 1- Analytical Hierarchy Process and TOPSIS, named AHP-TOPSIS, and 2- Modified Digital Logic and TOPSIS, named MDL-TOPSIS. Data is analyzed by Expert Choice. 11.
Based on considered error level of 5%, results of both AHP-TOPSIS and MDL-TOPSIS methods, with closeness index values of 0.893 and 0.873 indicated that Al Zahra hospital provides the best quality of services.
The Al Zahra hospital has acceptable performance rather than other hospitals. It is suggested that MDL-TOPSIS and AHP-TOPSIS methods be applied to all hospitals in the country in order to identify the strengths and weaknesses so that hospitals recognize their overall status among the other hospitals compared.

Renewable energy types such as solar, wind or geothermal energy have been increasingly considered by different countries over the last few years in order to diversify power sources, reduce dependence on one single of energy, and achieve sustainable energy. On the other hand, rising prices of fossil fuels and the fact that they are finite, environmental pollution and evolution of the related technologies have drawn attention to renewable energy. This paper identifies economical, environmental, social and technical aspects of quantitative and qualitative criteria for renewable-power plant. Then a hybrid method of a Modified Digital Logic and fuzzy VIKOR is presented to weight the criteria and prioritize renewable-power plants. To illustrate the proposed method, a case study in the country Iran is presented; in which five types of renewable-power plants are evaluated. Results suggest that the priorities according to the criteria are hydroelectric, geothermal, wind, biomass and photovoltaic power plants, respectively.

Avoidance of turning natural disasters to natural tragedies requires upraising in capacitance of management and planning in Hazard management. Into this purpose, seconds and minutes should be considered as an essential limitation to save lives in such natural catastrophes in the process of serving. To this end, planning for the optimal use of available time of relief system in these cases, will lead to increased backup capabilities, assistance in the shortest possible time, and the appropriate allocation of resources to the required people. In this regard, the present study tries to provide a model for distributing relief tasks in different regions of a city, between hospitals and relief centers, and considering the relief funds assigned to them for relief, and use of real distances in different parts of the city of Qazvin. These centers, will focus on optimizing the time needed to transfer injured people in crisis situations to hospitals, in a three-stage supply chain, and, in order to achieve these goals, consider the capacity of the fleet in the problem. Degree of complexity of the problem is NP-hard.Therefore, finding an optimal solution in a reasonable time is impossible by using accurate methods. In This paper, a dynamic genetic algorithm has been employed in which contains chromosomes with variable structure in order to solve the problem. In addition, for evaluation of results accuracy from this algorithm, it compare with result from random search method. Results show genetic algorithm is more reliable and demonstrate the improvement of average results with increase of relay vehicle and capacity of them; also the deterioration of average results with growth of injured people.

Fuel consumption is one of the main contemporary issues in transportation sector. Because the fuel is subsidized in Iran, reducing fuel consumption has benefits for both the government and private sector. One of the most important areas of fuel consumption is the industry scope. In this area, reducing fuel consumption has important benefits such as reducing the total costs of finished products and increasing its competitiveness capability. One the other hand, focusing on the reduction of fuel consumption, could make disruptions in transportation of production scheduling. The present study introduces a model for reducing fuel consumption in manufacturing of finished goods, considering production and transportation scheduling. The proposed model consist of components such as comprehensive decision-making in suppliers production scheduling, shared transportation and integration of production and transportation scheduling. In order to evaluate the effectiveness of the proposed model, it is compared with two conventional models in the manufacturing sector. To achieve a comprehensive result, comparisons have been made on a wide range of different cases. The Results show that the proposed model is superior and better than the current models in production and transportation scheduling.

One of the most important aspects of designing a supply chain is the matter of supplier selection. It’s a complicated issue because suppliers should satisfy some criteria and ranking those leads to a MCDM problem. Therefore, a structured and systematic approach is required to solve this problem. In this article, we address supplier selection problem in advertising industry and propose two new criteria. Correspondingly, in order to evaluate suppliers in the industry a hybrid approach is proposed which combines fuzzy AHP with fuzzy TOPSIS techniques. Each method has its cons and pros we try to use the advantages of the both methods in the proposed hybrid approach. On the other hand, the related parameters in this decision making problem are qualitative. Some errors could happen in transformation of the qualitative parameters to quantitative ones. Accordingly, in transforming procedure we use fuzzy theory to reduce these errors.

Iran's banking system nowadays, is facing new challenges in joining the World Trade Organization (WTO), i.e. foreign banks and private banks entering the system and rises in financial and credit institute's activities. On the other hand, following the implementation of administrative system general policies, the banking system will also conform to it. In this paper, in order to rank the banks, several indexes are determined. The ranking provides a competitive environment for the banks to implement these policies properly. The indexes are defined according to recent researches in foreign countries and indexes of Balanced Scorecard method and corporate social responsibility attributes are considered. After identifying 6 main criteria and 25 sub criteria their weights are determined by the Analytical Hierarchy process (AHP) based on a sample of 8 experts. Thereafter, the score of each bank in each sub criteria is identified by use of financial information of the considered banks, experts and banks customers. Finally, the considered banks are prioritized using Fuzzy TOPISIS method. Results show financial aspect with a weight equal to 22 percent and social aspect with a weight equal to 16 percent are the most and less important, correspondingly. in sub-indexes, a return of investment with the weight of 0.096, reducing the operation cycle time with the weight of 0.094, net income ratio with the weight of 0.079 and less energy consumption with the weight of 0.073 are the most the most important, respectively.

In this paper a scheduling problem in a 2-stage supply chain is discussed. Suppliers are in the first stage and in the second stage, there are vehicles which carry orders to a manufacturing center. The purpose is to allocate orders to suppliers, sequence the suppliers’ production, allocate orders to transport vehicles and prioritize orders that should be carried by vehicles to minimize the total time of the process and transportation. This issue has not yet been discussed in the literature. First, a mixed integer programming mathematical model is presented. Then, in order to solve the problem, a new algorithm is proposed which is a new combination of genetic and Simulated Annealing Algorithms. To evaluate the performance of the algorithm, it is compared with one of the algorithms presented in the literature, genetic algorithm and simulated annealing algorithm, separately. Comparison results indicate the advantage of the proposed algorithm in comparison with other algorithms.

Nowadays, the application of effective and efficient decisions on complex issues require the use of decision support systems. This Paper provided a decision support system based on the genetic algorithm for production and transportation scheduling problem in a supply chain. It is assumed that there are number of orders that should be produced by suppliers and should be transported to the plant by a transportation fleet. The aim is to assign orders to the suppliers, specify the order of their production, allocate processed orders to the vehicles for transport and to arrange them in a way that minimizes the total delivery time. It has been shown that the complexity of the problem was related to Np-hard and there was no possibility of using accurate methods to solve the problem in a reasonable time. So, the genetic algorithm was used in this paper to solve the problem. By using this decision support system, a new approach to supply chain management was proposed. The analysis of the approach proposed in this study compared to the conventional approaches by the decision support system indicated the preference of our proposed approach.