Mohammad saeed Company; Parham Azimi
Abstract
In this study, the use of simulation technique in bi-objective optimization of assembly line balancing problem has been studied. The aim of this paper is to determine optimal allocation of human resource and equipment to parallel workstations in order to minimize the cost of adding equipment and manpower ...
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In this study, the use of simulation technique in bi-objective optimization of assembly line balancing problem has been studied. The aim of this paper is to determine optimal allocation of human resource and equipment to parallel workstations in order to minimize the cost of adding equipment and manpower among the stations and maximize the production output. In other words, with optimal use of resources, production output is maximized and therefore productivity become maximum. To this end, with optimization via simulation, the production line process is simulated in the form of a simulation model in the ED software. After validating the simulation model using design of experiment, various scenarios designed and run in the simulation model. Possible results for human resource and equipment variables, obtained by genetic algorithm are shown in a Pareto chart and have compared with the production line current situation
Majid Esmaelian; Sayedeh Maryam Abdollahi
Abstract
Course timetabling is an important branch of the general scheduling problem. The course timetabling problem as a step in the course planning process in universities is one of the challenges faced by managers in the field of education. The problem is defined as assigning university courses to specific ...
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Course timetabling is an important branch of the general scheduling problem. The course timetabling problem as a step in the course planning process in universities is one of the challenges faced by managers in the field of education. The problem is defined as assigning university courses to specific periods throughout a week for a given semester while satisfying specific constraints. In this study, we present two novel binary integer linear programming models for the university timetabling problem. Using a GAMS IP Solver, several experiments through each model are solved and the results (the number of the decision variables and solution time) are compared and analyzed. The computational comparison indicates that the second model can be used for modeling large-scaled problems and has less computational and size complexity. Therefore, the second model is applied to optimal scheduling the courses planned for the faculty of administrative science and economics (ASE) at Isfahan University for one semester and the results consist of table of courses planned for teachers, students groups, rooms and workdays are presented
Alireza Alinezhad; Niki Jalili Taghavian
Volume 13, Issue 39 , January 2016, , Pages 115-144
Abstract
Improving products quality and services is the best and most important factor to win competitors and get majority of the market share. In this regard, Failue mode and Effect analysis is an efficient tool to improve the quality products. Considering many criticisms to taraditional method, the risk priority ...
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Improving products quality and services is the best and most important factor to win competitors and get majority of the market share. In this regard, Failue mode and Effect analysis is an efficient tool to improve the quality products. Considering many criticisms to taraditional method, the risk priority number in FMEA is formed by multiplying of three factors (seveirity, Occurrence and Detect). In order to existing defects, a new method to calculate the risk priority number in FMEA based on data envelopment analysis method is introduced. The aim of this study is to provide a new kind of risk priority number by assigning different weights to each of the risk factors. Also according to severity, Occurance and detection numbers that are achieved by a team of experts and are not a constant and certain factor, in this research has been used Robust optimization because of covering the result of DEA and less complexity. The results of example indicate that, proposed model is more effective than traditional RPN and provide a full ranking.
