A linear-time crystal-growth algorithm for discretization of continuum approximation

Continuous approximation is regarded as a scalable and insightful method for acquiring near-optimum solutions to various location problems. A continuous solution nonetheless only density function further discretization procedure needed obtain discrete engineering practice. Inspired by the process of “crystal growth”, this paper proposes constructive heuristic algorithm an alternative classic meta-heuristic disk (Ouyang Daganzo, 2006) in discretizing from continuum model. The main idea rasterize space into set small cells (either regular triangles or squares) repeatedly grow core cell full-service area according certain visiting sequence. Thus, it has linear time complexity proportional number space. Numerical examples are conducted test performance proposed algorithm. results indicate that can solve facility locations more efficiently exhibits robust compared with