Authors:
István Módos
1
;
Kiryl Kalodkin
1
;
Přemysl Šůcha
2
and
Zdeněk Hanzálek
2
Affiliations:
1
Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University in Prague, Czech Republic, Department of Control Engineering, Czech Technical University in Prague and Czech Republic
;
2
Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University in Prague and Czech Republic
Keyword(s):
Scheduling, Dedicated Machines, Energy Consumption Limits.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Operational Research
;
Optimization
;
Pattern Recognition
;
Scheduling
;
Software Engineering
;
Symbolic Systems
Abstract:
This work studies a problem of scheduling non-preemptive independent jobs on dedicated machines while considering an energy consumption limit. The problem is motivated by energy-demanding production processes, such as glass tempering and steel hardening, in which a material is heated to high temperature in furnaces. The production companies have contracts with electric utilities that specify a maximum energy consumption limit. If the heating in the furnaces is not planned carefully, the energy spikes overshoot the energy consumption limit, and the companies must pay large penalty fees. In this paper, we propose two exact methods that find schedules with the minimum makespan such that the energy limit is satisfied. The first proposed method is a Constraint Programming model and the second one finds the optimal solution by iteratively re-solving a Mixed Integer Linear Programming model with a decreasing scheduling horizon. The iterative algorithm exploits the fact that the start times
do not need to be modeled explicitly, which leads to an efficient method for solving instances with a higher number of shorter jobs. The experimental results show that our methods outperform an adapted approach from the literature for a related problem.
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