Mixed Energy and Production Scheduling in an Eco-Industrial Park

In recent times, eco-industrial parks (EIP) have taken on a significant role in addressing environmental challenges and supporting sustainable practices. To enhance the efficient utilization of energy within the park and ensure the achievement of production targets among its members, the implementation of energy and production scheduling is imperative. This paper addresses this optimization challenge by formulating it into a constraint programming (CP) model. The optimized scheduling solutions generated by the CP model will be directly used to guide the operations within the simulation environment of the EIP. The paper compares the CP results with the results of another method which we developed in our previous research stage. The outcomes of CP solver demonstrate its effectiveness in optimizing energy utilization and meeting production targets. This research contributes to developing a practical decision support system for resolving real-life scheduling problems in industry parks.

Authors

Institutions

Publication Details

Published
2024-12-15
DOI
https://doi.org/10.1109/wsc63780.2024.10838872
Citations
1
Primary Topic
Sustainable Industrial Ecology
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mixed Energy and Production Scheduling in an Eco-Industrial Park

Shufang Xie, Tao Zhang, Björn Vollack, Tobias Uhlig et al.
1 citations
Sustainable Industrial Ecology
0.35
article

Mixed Energy and Production Scheduling in an Eco-Industrial Park

Shufang Xie, Tao Zhang, Björn Vollack, Tobias Uhlig, Oliver Rose
article en
1 citations

Abstract

In recent times, eco-industrial parks (EIP) have taken on a significant role in addressing environmental challenges and supporting sustainable practices. To enhance the efficient utilization of energy within the park and ensure the achievement of production targets among its members, the implementation of energy and production scheduling is imperative. This paper addresses this optimization challenge by formulating it into a constraint programming (CP) model. The optimized scheduling solutions generated by the CP model will be directly used to guide the operations within the simulation environment of the EIP. The paper compares the CP results with the results of another method which we developed in our previous research stage. The outcomes of CP solver demonstrate its effectiveness in optimizing energy utilization and meeting production targets. This research contributes to developing a practical decision support system for resolving real-life scheduling problems in industry parks.

Universität der Bundeswehr München (DE), Technische Universität Dresden (DE)
Openalex Percentile: Top 31%
Sustainable Industrial Ecology
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.