期刊
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
卷 56, 期 5, 页码 2076-2098出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2017.1351638
关键词
production scheduling; flow shop; renewable energy; energy consumption; wind power
资金
- Doctoral Program of the German Academic Exchange Service (DAAD)
- Directorate For Engineering
- Div Of Chem, Bioeng, Env, & Transp Sys [1512217] Funding Source: National Science Foundation
Over the last decade, manufacturing companies have identified renewable energy as a promising means to cope with time-varying energy prices and to reduce energy-related greenhouse gas emissions. As a result of this development, global installed capacity of wind power has expanded significantly. To make efficient use of onsite wind power generation facilities in manufacturing, production scheduling tools need to consider the uncertainty attached to wind power generation along with changes in the energy procurement cost and in the products' environmental footprints. To this end, we propose a solution procedure that first generates a large number of wind power scenarios that characterise the variability in wind power over time. Subsequently, a two-stage stochastic optimisation procedure computes a production schedule and energy supply decisions for a flow shop system. In the first stage, a bi-objective mixed integer linear programme simultaneously minimises the total weighted flow time and the expected energy cost, based on the generated wind power scenarios. In the second stage, energy supply decisions are adjusted based on real-time wind power data. A numerical example is used to illustrate the ability of the developed decision support tool to handle the uncertainty attached to wind power generation and its effectiveness in realising energy-related objectives in manufacturing.
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