An Effective Hybrid Sine Cosine Algorithm to Minimize Carbon Emission on Flow-shop Scheduling Sequence Dependent Setup

Author:

Marsetiya Utama Dana

Abstract

Recently, carbon emissions have become a major environmental problem. In the industrial sector, carbon emissions account for half of the world's total carbon emissions. This article discusses the issue of scheduling Flow Shop Sequence Dependent Setup (FSSDS). It aims to minimize carbon emissions. The algorithm proposed is the Hybrid Sine Cosine Algorithm (HSCA) to solve FSSDS problems to reduce carbon emissions. We offered one of some search agents in the SCA use NEH.  The algorithm is used for some test different jobs and machines. Several experiments were carried out to test the parameters and effectiveness of the algorithm. The parameters used in the trial are population and iteration. As a result, several parameters were proposed to HSCA to minimize carbon emissions. In the effectiveness test, the HSCA showed better performance compared to the simulated annealing and cross-entropy algorithm.

Publisher

Universitas Muhammadiyah Malang

Subject

General Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3