Journal of Optimization in Industrial Engineering
Volume:11 Issue: 24, Summer and Autumn 2018

The current electricity demand is increasing, and now the government has involved third parties in the implementation of electricity so that investors compete in building infrastructure in order to apply electricity. Thermal power is one source that has a fast break event point compared to other resources that more interested investors even with all forms of pollution caused. A form of heat power using a vapor pressure is fired into the turbine so that it will cause a rotating force that will turn the generator into an electric generator. thermal power has the ability to generate electricity large, but if there is a failure in operation, then the burden will quickly lose power sources that can cripple production activities.FMEA is one of the most widely used tools in the industry to analyze the root cause of the system so that the system is protected from small and large damage and can disrupt the stability of the industrial operating system. The reliability of the machine must always be maintained so that with this method it is expected to help the power service providers to maintain the availability of its services.With the implementation of FMEA, we get an overview of the steps to be taken for the future so that the reliability of a steam generator boiler system can be improved

Many criteria have been presented so far for innovation measurement. Presenting the relation between input and output of innovation, completing other criteria and achieving more comprehensive criteria has also been raised. What is of vital importance is the right utilization of these criteria towards measuring innovation. This paper seeks to present a model to measure innovation that, in addition to the simplicity of its perception and measurement method, has an adequate comprehensiveness. The analyses are undertaken through two real case studies in automotive industry in Iran. The results show that Saipa automotive company should concentrate on Info-ware, Orga-ware and Human-ware while Iran-khodro automotive company needs to focus on Info-ware, Orga-ware and Techno-ware aspects to balance the innovation processes.

Petroleum (crude oil) is one of the most important resources of energy and its demand and consumption is growing while it is a non-renewable energy resource. Hence forecasting of its demand is necessary to plan appropriate strategies for managing future requirements. In this paper, three types of time series methods including univariate Seasonal ARIMA, Winters forecasting and Transfer Function-noise (TF) models are used to forecast the petroleum demand in OECD countries. To do this, we use the demand data from January 2001 to September 2010 and hold out data from October 2009 to September 2010 to test the sufficiency of the forecasts. For the TF model, OECD petroleum demand is modeled as a function of their GDP. We compare the root mean square error (RMSE) of the fitted models and check what percentage of the testing data is covered by the confidence intervals (C.I.). Accordingly we conclude that Transfer Function model demonstrates a better forecasting performance.

In this research, the factors affectinguniversity employees’ motivation and productivity are identified and classified in seven groups; the impact of each motivation factor on the productivity is presented by ANP fuzzy model.Eight universities in Iran were analyzed in this research work. The aim of this study is to explore the productivity of employees. This paper attempts to give new insights intodesigning the portfolio factors, motivating employees for productivity improvement by implementing BLP and ANP fuzzy models.The research results show that there is a positive and significant relationship among reward system, motivation factors, and human resources productivity. In addition, among the options of reward system, the factors of internal (inherent) reward, non-financial external reward, and financial external reward had the highestimpact on increasing motivation and productivity factors. At the next stage, a BLP model is designed according to the importance and impact of each reward system option on motivation and productivity factors and organization limitations, including budget, facilities, and conditions to design portfolio factors motivating employees with the aim of improving productivity. The research results show that actualizing performance evaluation, receiving the feedback from the results of doing tasks by different ways, providing an opportunity for all employees to progress, coordination between job specifications and employees’ abilities, and a manager competency are very critical for improving the organization productivity.

This paper presents a competitive supply chain network design problem in which one, two, or three supply chains are planning to enter the price-dependent markets simultaneously in uncertain environments and decide to set the prices and shape their networks. The chains produce competitive products either identical or highly substitutable. Fuzzy multi-level mixed integer programming is used to model the competition modes, and then the models are converted into an integrated bi-level one to be solved, in which the inner part sets the prices in dynamic competition and the outer part shapes the network cooperatively.Finally, a real-world problem is investigatedto illustrate how the bi-level model works and discuss how price, market share, total income, and supply chain network behave with respect to key marketing activities such as advertising, promotions, and brand loyalty.

This study deals with the effects of a supply chain (SC) with single product, multiple retailers and a manufacturer, where the manufacturer(he) produces lotsize of the product that contains a random portion of imperfect quality item. The imperfect quality products are sold in a secondary shop. The new contribution of this paper is a new non-linear demand function. Demand of the end customers varies with pricing and promotional effort of the rivalry amongst the retailers which can be used for the electronic goods, new lunched products, etc. We investigate the behavior of the supply chain under Manufacturer-Stackelberg(MS), and Retailer-Stackelberg(RS) model structures. The nature of the mentioned models provides great insights to a firm’s manager for achieving optimal strategy in a competitive marketing system. Within the framework of any bilevel decision problem, a leader's decision is influenced by the reaction of his followers. In MS model structure, following the method of replacing the lower level problem with its Kuhn-Tucker optimality condition, we transform the nonlinear bilevel programming problem into a nonlinear programming problem with the complementary slackness constraint condition. The objective of this paper is to determine the optimal selling price and promotional effort of each retailer, while the optimal wholesale price of the perfect quality products are determined by the manufacturer so that the above strategies are maximized. Finally, numerical examples with sensitivity analysis of the key parameters are illustrated to investigate the proposed model.

This paper considers the problem of minimizing make-span and maximum tardiness simultaneously for scheduling jobs under non-identical job sizes, dynamic job arrivals, incompatible job families,and sequence-dependentfamily setup time on the single batch- processor, where split size of jobs is allowed between batches. At first, a new Mixed Integer Linear Programming (MILP) model is proposed for this problem; then, it is solved by -constraint method.Since this problem is NP-hard, a bi-objective genetic algorithm (BOGA) is offered for real-sized problems. The efficiency of the proposed BOGA is evaluated to be comparedwith many test problemsby -constraint method based on performance measures. The results show that the proposed BOGAis found to be more efficient and faster than the -constraint method in generating Pareto fronts in most cases.

One of the main challenges for transportation engineers is the consideration of pedestrian safety as the most vulnerable aspect of the transport system. In many countries around the world, a large number of accidents recorded by the police are composed of accidents involving pedestrians and vehicles, for example when pedestrians may be struck by passing vehicles when crossing the street. Careful consideration of the parameters that are involved in selecting the type and optimum location of pedestrian crosswalks results in a higher pedestrian safety coefficient and a reduced accident rate at these facilities. At the start of this study, these parameters that are important in specifying the optimum type and location of pedestrian crosswalks were determined. Then the data layers of these identified parameters were defined using the ArcGIS software. These layers can subsequently be used for determination of the optimal positioning of pedestrian crosswalks. To specify the boundary changes for each parameter, fuzzy membership functions were defined for each parameter using fuzzy logic. The Analytical Hierarchy Process method (AHP) was used in order to combine these layers of information after the fuzzy membership functions were defined. Expert Choice software was used to determine the final weight resultant of the professional's poll that was conducted. A field study sample has been carried out to determine the optimal location of pedestrian crosswalks in the city of Tehran. The final output from the ArcGIS software shows the ideal locations and the appropriate type of pedestrian crosswalks in the field study sample. The results indicate that the use of fuzzy logic in definition of membership functions of location parameters, along with using AHP for determination of the weight of data layers built in ArcGIS, is a satisfactory combined method for specifying the location of pedestrian crosswalks.

In this paper one of the important “end of life options” (remanufacturing) has been analysed. Among the related studies surveyed the various remanufacturing aspects, less attention has been paid to the stochastic process routing. In this regard, a remanufacturing process routing with stochastic activities is modelled as a GERT network. One of the efficient ways to analyse a remanufacturing process is the identification of most effective activities based on the cost and time of the process during the process implementation. Criticality indexes are suitable scales for this purpose. Therefore, to analyse the important aspects of the remanufacturing process, four criticality indexes are developed in this paper. These indexes measure the cost and time of the process and its activities to identify the activities with high importance in terms of cost and time. On the other hand, simulation is an efficient tool to cope with the uncertainties in the production problems. Hence a Monte Carlo approach (which is developed using Arena software) has been adopted to analyse the GERT based model and to calculate the criticality indexes. In addition, a mathematical approach using Moment Generation Functions has been adopted to calculate the expected value of the criticality indexes. In addition, a numerical example (lathe spindle remanufacturing) has been solved using both proposed approaches. Results show the acceptable performance of the proposed GERT based simulation approach.

In this paper after a review on the concept and literature of knowledge management, the conceptual model of a successful knowledge management system that is currently being applied in a research and development (R&D) aerospace organization is presented and discussed. The main contribution of the paper is presenting the model in its useful and practical status without becoming involved in theoretical discussions that have different shapes but similar meanings.

This paper introduces a novel multi-objective evolutionary algorithm based on cat swarm optimizationalgorithm (EMCSO) and its application to solve a multi-objective knapsack problem. The multi-objective optimizers try to find the closest solutions to true Pareto front (POF) where it will be achieved by finding the less-crowded non-dominated solutions. The proposed method applies cat swarm optimization (CSO), a swarm-based algorithm with ability of exploration and exploitation, to produce offspring solutions and uses thenon-dominated sorting method to findthe solutionsas close as to POFand crowding distance technique toobtain a uniform distribution among thenon-dominated solutions. Also, the algorithm is allowedto keep the elites of population in reproduction processand use an opposition-based learning method for population initialization to enhance the convergence speed.The proposed algorithm is tested on standard test functions (zitzler’ functions: ZDT) and its performance is compared with traditional algorithms and is analyzed based onperformance measures of generational distance (GD), inverted GD, spread,and spacing. The simulation results indicate that the proposed method gets the quite satisfactory results in comparison with other optimization algorithms for functions of ZDT1 and ZDT2. Moreover, the proposed algorithm is applied to solve multi-objective knapsack problem.

Production is a key economic activity with potential long-term social benefits that can be thoroughly realised only if governments comply with their duties towards domestic production. Governments are responsible for the production of sustainable agricultural products via appropriate allocation of subsidies and regulation of price policies that would help take advantage of the potentials underlying agricultural production. In this paper, a model is developed to investigate the interaction between two decision makers in the stackelberg game, government as leader and agriculture as follower, with the ultimate aim of providing benefits to all sectors in the society in the sustainable agriculture paradigm. The proposed model is validated and its efficiency demonstrated via a case study of cotton production as a strategic agricultural production. The model is first solved using a combination of fuzzy mathematical and grey quadratic programming methods to account for the inherent uncertainty in a number of problem parameters. The model is then analyzed against various government-producer interaction scenarios and finally, the analysis results are compared.

Equipping hospital beds uses a great deal of a hospital''''s resources. Therefore, it is essential to consider the hospital beds'''' efficiency. To increase its efficiency, a fuzzy unrestricted model for managing hospital expenses is presented in this paper. The lack of beds in hospitals leads to patients’ admission loss and consecutively profit loss. On the other hand, increasing the bed count leads to an increase in equipment expenses. Therefore, in order to determine optimal bed capacity, it is of utmost importance to consider these two costs simultaneously. In our paper, hospital admission system is modeled with a multi-server queuing system (M/M/K). Therefore, to calculate the total cost function, limiting probabilities of multi-server queueing model is used. Furthermore, due to uncertain nature of parameters, such as interest rate and hospitalization profit in various future time periods, these uncertainties are covered by fuzzy logic. Finally, to determine the optimal bed count, Lee and Li''''s fuzzy ranking method is used. This model is implemented ona case study. Its goal is to determine the optimal bed count for emergency unit of Razi hospital in Torbat Heydarieh. Considering the high capability of Markovian chains in modeling different circumstances and the various queueing models, the proposed model can be extended for various hospital units.

Location is an important factor in the activity of economic enterprises. Owing to the importance, location-based sciencesought/seeks to provide the methods in order to determine and select the optimal location in the activities of enterprises. Enterprises seek to use scientific methods to maximize the services and efficiency and minimize the costs. Suitable location plays an important role in many fields such as reducing the costs and increasing the customer satisfaction. Location studies have been proposed in recent years as one of the key elements in the success and survival of industrial centers as considered at many national and international levels. This study, as an applied research, provides a new framework in location of ATMs using multi-criteria decision-making approach and fuzzy AHP and fuzzy ELECTRE III. The multi-criteria decision-making approaches were based on similar studies in other countries and viewpoints of experts and managers of Shahr Bank branches in Tehran, 1st District Municipality, and the establishment of favorable sites was identified by combining the information in order to influence the location of ATMs including competitors (0.202), price of land (0.199), access to facilities and utilities, poles and important centers of town (0.189), quality of track (0.180), security (0.120), transport and traffic (0.112), population under coverage (0.065), and regulation (0.039). At the end, the most appropriate locations of establishment of ATMs were determined to cover the demands of Tehran, 1st District Municipality using fuzzy AHP methods and ELECTRE III.

The main goal of this research is to identify the effective factors on tax evasion by fuzzy DEMATEL-method in Iran. At the present time tax evasion is one of the economic problems in developing countries. Our country has had in this problem for several decades. In this paper, we attempted to determine effective factors in tax evasion, and the relational structure of these factors is examined by fuzzy DEMATEL-method, and meanwhile to recognize their interaction, the hierarchy of the influence of these factors should be known, too. research results showed that among the effective factors, lack of law-makers, of dominance interference institutions which are not charge and the vast exemptions have the highest impact on tax evasion.