Heuristic Approach for RTTP Sample Clauses

Heuristic Approach for RTTP. RPBSA‌ The Population-Based Simulated Annealing method (PBSA) (Xxx Xxxxxxxxxx & Vergados, 2007) leverages TTSA (Anagnostopoulos et al., 2006), a simulated annealing algorithm for the TTP. This dissertation focuses on adapting the TTSA to enable its usage in a time-relaxed environment, this adapted algorithm will be called RTTSA . Since experimental findings show that PBSA delivers added value, it is appended as an additional step together with the RTTSA. This is done to obtain comparable results with the current best known solutions for the RTTP-instances (Xxxxxxx & Xxxxxxx, 2014; Xxxxx-Xxxxxxx & Xxxx, 2015). In the rest of this dissertation, the term RPBSA is used to refer to the PBSA method with RTTSA as underlying simulated annealing algorithm. While substantial effort is undertaken to adapt the TTSA algorithm to a time-relaxed setting, the components of PBSA are implemented as-is. Indeed, the framework of the PBSA algorithm makes no assumptions on the underlying simulated annealing algorithm, and thus needs no adaption when applying the RTTSA algorithm instead of the TTSA algorithm. It is sufficient to say that PBSA is used to enhance the performance of RTTSA. This section will first discuss the fitness evaluation of a given schedule (Section 4.1.1) and will then deliver an overview of the main concepts of RTTSA (Section 4.1.2). The next part of this section covers a short overview on the implementation of RPBSA (Section 4.1.3) and the generation of an initial schedule (Section 4.1.4). Finally, the different adaptations made to the TTSA algorithm are highlighted (Section 4.1.5). A more detailed overview of TTSA can be found in previous literature (Anagnostopoulos et al., 2006).