![]() ![]() In addition, several modifications of this method were proposed, such as late acceptance randomised descent algorithm (Abuhamdah 2010) and multi-objective late acceptance algorithm (Vancroonenburg and Wauters 2013). 2015), travelling purchaser problem (Goerler et al. A number of authors have published their own studies on LAHC applied to different problems, such as lock scheduling (Verstichel and Vanden Berghe 2009), liner shipping fleet repositioning (Tierney 2013), balancing two-sided assembly lines (Yuan et al. It was demonstrated that LAHC was able to work well in situations where the other two heuristics failed to produce good results.Īlthough LAHC is a relatively new algorithm, its unique characteristics attracted a particular attention of the research community. This provided the method with effectiveness and reliability. Also, it was found that despite apparent similarities with other local search metaheuristics such as simulated annealing (SA) and great deluge algorithm (GDA), LAHC had the underlying distinction, namely it did not require a guiding mechanism like, for example, cooling schedule in SA. First, its total search/convergence time was proportional to the history length, which was essential for its practical use. An extensive study of LAHC was carried in (Burke and Bykov 2012) where the salient properties of the method have been discussed. The number of the backward iterations is the only LAHC parameter referred to as “history length”. The main idea of LAHC is to compare in each iteration a candidate solution with the solution that has been chosen to be the current one several iterations before and to accept the candidate if it is better. The SCHC has shown the strongest performance on the most of our benchmark problems used.Ī single-parameter local search metaheuristic called late acceptance hill climbing algorithm (LAHC) was proposed by Burke and Bykov ( 2008). In this study, we compare the new method with late acceptance hill climbing, simulated annealing and great deluge algorithm. However, our new method has two additional advantages: a more flexible acceptance condition and better overall performance. Our experiments demonstrate that the proposed method shares the main properties with the late acceptance hill climbing method, namely its convergence time is proportional to the value of its parameter and a non-linear rescaling of a problem does not affect its search performance. In this paper, we investigate the behaviour of the three basic variants of SCHC on the university exam timetabling problem. Furthermore, the counting of steps can be organised in different ways therefore, the proposed method can generate a large number of variants and also extensions. This is the only parameter in the method that should be set up by the user. ![]() It is a very simple method in which the current cost serves as an acceptance bound for a number of consecutive steps. This paper presents a new single-parameter local search heuristic named step counting hill climbing algorithm (SCHC). ![]()
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