A histogram estimation of distribution algorithm for resource scheduling

Abstract

Resource scheduling is always a highly concerned NP-hard problem in operations research. Taking advantage of estimation of distribution (EDA) algorithms, this paper develops a histogram EDA (HEDA) for resource scheduling. First, a histogram-based distribution model is adopted. The height of each bin in the histogram is updated using the accumulation strategy according to the ranking of individuals. Second, a repair strategy is applied to fix all the newly sampled solutions into feasible ones that satisfy the deadline constraint. Experimental results show that the proposed HEDA is promising, particularly in large-scale instances. © 2018 Copyright held by the owner/author(s).