Combinatorial optimization for job sequencing with one common and multiple secondary resources by using a SAT solver augmented with a domain-specific heuristic
A. Pugatšov (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Emir Demirović – Mentor (TU Delft - Algorithmics)
K. Sidorov – Mentor (TU Delft - Algorithmics)
Maarten Flippo – Mentor (TU Delft - Algorithmics)
J.E.A.P. Decouchant – Graduation committee member (TU Delft - Data-Intensive Systems)
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Abstract
This paper solves job sequencing with one common and multiple secondary resources (JSOCMSR) problem by encoding it as a Boolean satisfiability (SAT) problem and applying domain-specific heuristics to improve the SAT solver’s performance. JSOCMSR problem is an NP-hard scheduling problem where each job utilizes two resources: a shared resource and a secondary job-dependent resource. First, the problem was modeled as an instance of SAT and then the SAT solver was augmented with a static greedy variable-ordering heuristic. This heuristic has led to significant improvement in the solver’s speed compared to a generic SAT heuristic for problem instances of larger size.