International Journal of Industiral Engineering & Producion Research
http://ijiepr.iust.ac.ir
International Journal of Industrial Engineering & Production Research - Journal articles for year 2014, Volume 25, Number 1Yektaweb Collection - https://yektaweb.comen2014/2/12Multi-Objective Scheduling Problem in a Three-Stage Production System
http://www.iust.ac.ir/ijieen/browse.php?a_id=515&sid=1&slc_lang=en
A three stage production system is considered in this paper. There are two stages to fabricate and ready the parts and an assembly stage to assembly the parts and complete the products in this system. Suppose that a number of products of different kinds are ordered. Each product is assembled with a set of several parts. At first the parts are produced in the first stage with parallel machines and then they are controlled and ready in the second stage and finally the parts are assembled in an assembly stage to produce the products. Two objective functions are considered that are: (1) to minimizing the completion time of all products (makespan), and (2) minimizing the sum of earliness and tardiness of all products (∑_i▒(E_i∕T_i ) . Since this type of problem is NP-hard, a new multi-objective algorithm is designed for searching locally Pareto-optimal frontier for the problem. To validate the performance of the proposed algorithm, in terms of solution quality and diversity level, various test problems are made and the reliability of the proposed algorithm, based on some comparison metrics, is compared with two prominent multi-objective genetic algorithms, i.e. NSGA-II and SPEA-II. The computational results show that performance of the proposed algorithms is good in both efficiency and effectiveness criterions.Parviz FattahiSystem Dynamics and Artificial Neural Network Integration: A Tool to Valuate the Level of Job Satisfaction in Services
http://www.iust.ac.ir/ijieen/browse.php?a_id=282&sid=1&slc_lang=en
Job Satisfaction (JS) plays important role as a competitive advantage in organizations especially in helth industry. Recruitment and retention of human resources are persistent problems associated with this field. Most of the researchs have focused on the job satisfaction factors and few of researches have noticed about its effects on productivity. However, little researchs have focused on the factors and effects of job satisfaction simultanosly by system dynamics approaches.In this paper, firstly, analyses the literature relating to system dynamics and job satisfaction in services specially at a hospital clinic and reports the related factors of employee job satisfaction and its effects on productivity. The conflicts and similarities of the researches are discussed and argued. Then a novel procedure for job satisfaction evaluation using (Artificial Neural Networks)ANNs and system dynamics is presented. The proposed procedure is implemented for a large hospital in Iran. The most influencial factors on job satisfaction are chosen by using ANN and three differents dynamics scenarios are built based on ANN's result. . The modelling effort has focused on evaluating the job satisfaction level in terms of key factors which obtain from ANN result such as Pay, Work and Co-Workers at all three scenarios. The study concludes with the analysis of the obtained results. The results show that this model is significantly usfule for job satisfaction evaluation
Keywords: Job Satisfaction, system dynamics, Artificial Neural Network (ANN), healthcar field.
Yahia zare mehrjerdiImplementation of Traditional (S-R)-Based PM Method with Bayesian Inference
http://www.iust.ac.ir/ijieen/browse.php?a_id=296&sid=1&slc_lang=en
In order to perform Preventive Maintenance (PM), two approaches have evolved in the literature. The traditional approach is based on the use of statistical and reliability analysis of equipment failure. Under statistical-reliability (S-R)-based PM, the objective of achieving the minimum total cost is pursued by establishing fixed PM intervals, which are statistically optimal, at which to replace or overhaul equipments or components. The second approach involves the use of sensor-based monitoring of equipment condition in order to predict occurrence of machine failure. Under condition-based (C-B) PM, intervals between PM works are no longer fixed, but are performed only “when needed”. It is obvious that Condition Based Maintenance (CBM) needs an on-line inspection and monitoring system that causes CBM to be expensive. Whenever this cost is infeasible, we can develop other methods to improve the performance of traditional (S-R)-based PM method. In this research, the concept of Bayesian inference was used. The time between machine failures was observed, and with combining Bayesian Inference with (S-R)-based PM, it is tried to determine the optimal checkpoints. Therefore, this approach will be effective when it is combined with traditional (S-R)-based PM, even if large number of data is gathered.Mohammad Saber Fallah NezhadA Holding Strategy to Optimize the Bus Transit Service
http://www.iust.ac.ir/ijieen/browse.php?a_id=433&sid=1&slc_lang=en
Bus systems are unstable without considering any control. Thus, we are able to consider some control strategies to alleviate this problem. A holding control strategy is one commonly used real-time control strategy that can improve service quality. This paper develops a mathematical model for a holding control strategy. The objective of this model is to minimize the total cost related to passengers at any stop. To solve the model, particle swarm optimization (PSO) is proposed. The results of the numerical examples show that the additional total cost caused by service irregularity is reduced by 25% by applying the presented holding model to the given problem.Reza Tavakkoli-MogahddamManufacturing Cell Configuration Considering Worker Interest Concept Applying a Bi-Objective Programming Approach
http://www.iust.ac.ir/ijieen/browse.php?a_id=465&sid=1&slc_lang=en
Generally, human resources play an important role in manufacturing systems as they can affect the work environment. One of the most important factors affecting the human resources is being an interactional interest among the workers in the workshops. If the workers in a manufacturing cell have the highest surface of the interactional interest level, it causes a significant raise in coordination and cooperation indicators and in long time periods. In this paper, a new concept of being an interactional interest between workers in a manufacturing cell besides the ability to work with its machines is proposed and a bi-objective mathematical model to carry out this new point of view in cellular manufacturing systems is presented. Applying the ε-constraint method as an optimization tool for multi-objective mathematical programming, a comprehensive numerical example is solved to exhibit the capability of the presented model.Iraj MahdaviA Two-Stage Hybrid Flowshop Scheduling Problem with Serial Batching
http://www.iust.ac.ir/ijieen/browse.php?a_id=416&sid=1&slc_lang=en
In this paper the problem of serial batch scheduling in a two-stage hybrid flow shop environment with minimizing Makesapn is studied. In serial batching it is assumed that jobs in a batch are processed serially, and their completion time is defined to be equal to the finishing time of the last job in the batch. The analysis and implementation of the prohibited transference of jobs among the machines of stage one in serial batch is the main contribution of this study. Machine set-up and ready time for all jobs are assumed to be zero and no Preemption is allowed. Machines may not breakdown but at times they may be idle. As the problem is NP-hard, a genetic algorithm is developed to give near optimal solutions. Since this problem has not been studied previously, therefore, a lower bound is developed for evaluating the performance of the proposed GA. Many test problems have been solved using GA and results compared with lower bound. Results showed GA can obtain a near optimal solution for small, median and large size problems in reasonable time.Rashed SahraeianA New Lower Bound for Flexible Flow Shop Problem with Unrelated Parallel Machines
http://www.iust.ac.ir/ijieen/browse.php?a_id=478&sid=1&slc_lang=en
Flexible flow shop scheduling problem (FFS) with unrelated parallel machines contains sequencing in flow shop where, at any stage, there exists one or more processors. The objective consists of minimizing the maximum completion time. Because of NP-completeness of FFS problem, it is necessary to use heuristics method to address problems of moderate to large scale problem. Therefore, for assessment the quality of this heuristic, this paper develop a global lower bound on FFS makespan problems with unrelated parallel machines.Nasim NahavandiA Multi Objective Optimization Model for Redundancy Allocation Problems in Series-Parallel Systems with Repairable Components
http://www.iust.ac.ir/ijieen/browse.php?a_id=476&sid=1&slc_lang=en
The main goal in this paper is to propose an optimization model for determining the structure of a series-parallel system. Regarding the previous studies in series-parallel systems, the main contribution of this study is to expand the redundancy allocation parallel to systems that have repairable components. The considered optimization model has two objectives: maximizing the system mean time to first failure and minimizing the total cost of the system. The main constraints of the model are: maximum number of the components in the system, maximum and minimum number of components in each subsystem and total weight of the system. After establishing the optimization model, a multi objective approach of Imperialist Competitive Algorithm is proposed to solve the model.Maghsoud Amiri