A Simulated Annealing based approach to solve the generator maintenance scheduling problem

Abstract

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Joint Maintenance and Production Operations Decision Making in Flexible Manufacturing Systems

“…SA was applied in the problem of scheduling maintenance for a thermal generator by Satoh and Nara [101]. More recently, Saraiva et al [102] proposed a SA based approach for the generator maintenance problem but with a different objective function than the one presented in [101].…”

Application of Improved Simulated Annealing Heuristics to Optimization Product Distribution and Waste Bottle Recycling

“…If the new solution improves the objective value, then it is accepted. If it is worse than the current one, it can still be accepted depending on a so-called probability of accepting worse solution [12]. The probability is obtained from the Boltzman distribution…”

The Application of a Computerised Decision Support System for Generator Maintenance Scheduling: A South African Case Study

“…Within the MIQP formulation, the problem instance has 114 975 variables and 164 258 constraints (or 279 233 if constraint sets (11) and (12) The best schedule obtained by the DSS is shown graphically in Figure 3. Notice that the schedule splits the maintenance into two parts over the year, corresponding to the times that have lower demand.…”

“…The first move operator (found in the GMS literature [16,11]), hereafter referred to as the 'classical' operator, generates a neighbouring solution by randomly selecting one unit and randomly changing its maintenance starting time to a new value within its allowed maintenance window.…”

“…In an exact solution approach, solution techniques include methods such as branch-and-bound algorithms, dynamic programming, and Benders' decomposition method [10]. Approximate solution approaches include solution techniques such as basic search heuristics, metaheuristics (including genetic algorithm [5], tabu search, simulated annealing [11], ant colony optimisation, particle swarm optimisation [12]), fuzzy logic modelling, and expert system approaches [13]. General purpose decision support systems such as the spreadsheet-based optimisation tool developed by Savić et al [14] may also be used to solve the GMS problem.…”