Peckish Initialisation Strategies for Evolutionary Timetabling
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
Three Methods to Automate the Space Allocation Process in UK Universities
PATAT '00 Selected papers from the Third International Conference on Practice and Theory of Automated Timetabling III
Asynchronous Cooperative Local Search for the Office-Space-Allocation Problem
INFORMS Journal on Computing
Selection mechanisms in memory consideration for examination timetabling with harmony search
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Nurse Scheduling Using Harmony Search
BIC-TA '11 Proceedings of the 2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications
Nurse rostering using modified harmony search algorithm
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part II
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Office-Space-Allocation problem is a distribution of a set of limited spaces to a set of resources subject to two types of constraints: hard and soft. Hard constraints must be fulfilled while the soft constraints to be satisfied as much as possible. The quality of the solution is determined based on satisfaction of the soft constraints and the best usage of spaces. The harmony search algorithm (HSA) is a population-based metaheuristic inspired by a musical improvisation process. At each iteration, three operators are used to generate the new harmony: memory consideration, random consideration, and pitch adjustment. In this paper, we modify the memory consideration operator to select from the best solution in the population during the search. HSA is evaluated by using three datasets from Nottingham, and Wolverhampton universities. Experimentally, the HSA obtained new results for two datasets, and a comparable result for the third dataset.