期刊
JOURNAL OF CLEANER PRODUCTION
卷 65, 期 -, 页码 87-96出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2013.07.060
关键词
Energy efficient production planning; Sustainable manufacturing; Job shop scheduling
Manufacturing enterprises nowadays face the challenge of increasing energy prices and requirements to reduce their emissions. Most reported work on reducing manufacturing energy consumption today focuses on the need to improve the efficiency of resources (machines) largely ignoring the potential for energy reducing on the system-level where the operational method can be employed as the energy saving approach. The advantage is clearly that the scheduling and planning approach can also be applied across existing legacy systems and does not require large investment. Therefore, a multi-objective scheduling method is developed in this paper with reducing energy consumption as one of the objectives. This research focuses on classical job shop environment which is widely used in the manufacturing industry. A model for the bi-objectives problem that minimises total electricity consumption and total weighted tardiness is developed and the Non-dominant Sorting Genetic Algorithm is employed as the solution to obtain the Pareto front. A case study based on a modified 10 x 10 job shop is presented to show the effectiveness of the algorithm and to prove the feasibility of the model. (C) 2013 The Authors. Published by Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据