Authors:
Abhishek Awasthi
1
;
Jörg Lässig
1
and
Oliver Kramer
2
Affiliations:
1
University of Applied Sciences Zittau/Görlitz, Germany
;
2
Carl von Ossietzky University of Oldenburg, Germany
Keyword(s):
Scheduling, Algorithms, Simulated Annealing, NP-Hard.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Industrial Applications of Artificial Intelligence
;
Operational Research
;
Problem Solving
;
Scheduling and Planning
Abstract:
This paper considers the un-restricted case of the Common Due-Date (CDD) problem with controllable
processing times. The problem consists of scheduling jobs with controllable processing times on a single
machine against a common due-date to minimize the overall earliness/tardiness and the compression penalties
of the jobs. The objective of the problem is to find the processing sequence of jobs, the optimal reduction
in the processing times of the jobs and their completion times. In this work, we first present and prove an
essential property for the controllable processing time CDD problem for the un-restricted case along with an
exact linear algorithm for optimizing a given job sequence for a single machine with a run-time
complexity of O(n), where n is the number of jobs. Henceforth, we implement our polynomial algorithm in
conjunction with a modified Simulated Annealing (SA) algorithm and Threshold Accepting (TA) to obtain the
optimal/best processing sequence while compari
ng the two heuristic approaches, as well. The implementation
is carried out on appended CDD benchmark instances provided in the OR-library.
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