Optimizing Shared Resources in a Batch Production Process using Genetic Algorithm for Small Production Industry for Different Batch Condition
Journal Title: IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE) - Year 2018, Vol 15, Issue 6
Abstract
Mathematical optimization is a process for finding and selecting the best fit values that is used to solve various engineering problems. Along with a complex area, it is important to improve productivity and efficiency for a company or even an industry. Based on a large number of literature reviews, intelligent scheduling methods are the most effective way to solve practical complex scheduling problems. The goal of this research is to increase the comprehensive production effectiveness for small production systems. The research is based on the actual demand of the production batch process and provides the ideal solution to the current problems. This approach considers the approach when randomly placed orders are deposited in the form of batches for production, and look for application of intelligent control under realistic conditions. As a result, it is important to develop a new model of production system which takes into account some obstacles. The problem that focuses on the production system is to reduce the time spent by the mathematical model. The optimization problem is solved using intelligent algorithms, which include Genetic Algorithm (GA) while providing some effective improvement strategies based on the lack of application.
Authors and Affiliations
Pushpendra Singh Chahar, Gaurav Kumar Chhaparwal, Raghav Singh Dhakar, Sharad Shrivastava
Keywords
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- EP ID EP438874
- DOI 10.9790/1684-1506022638.
- Views 47
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