Mate-Heuristic Algorithms For Solving The Facility Layout Problem And Focused Crawler Technology

Mate-heuristic algorithms and their applications have been the focus in the field of computational science.Studies have shown that Mate-heuristic algorithms are very effective for solving NP-hard problems and optimizing the performance and quality of information retrieval technology.Facility layout problem(FLP)belongs to NP-hard problems,and the reasonable layout of the production workshop can effectively improve the production efficiency of enterprise.There is no accurate and effective method to solve the global optimal solution of FLP problems.For the focused crawler(FC)technology in information retrieval technology,which aims to capture as many webpages as possible with a specific topic from the entire Web,it is important to optimize the global search capability of this crawling technology.This paper mainly studies multi-row dynamic facility layout problem(DFLP)and focused crawling search strategy.We propose some mate-heuristic algorithms to solve multi-row DFLP problems and improve the search performance of focused crawler.The concrete research contents and methods are as follows:1)For the multi-row DFLP problem,this paper proposes a modified genetic algorithm(mGA)and backtracking search algorithm(BSA)to solve it.Firstly,mGA improves the diversity of the GA by combining the adaptive partial mapping crossover(PMX)and adaptive mixed multiple mutation strategies.Secondly,for a new evolutionary algorithm——BSA algorithm,due to its unique initialization,crossover and mutation mechanisms and stronger “memory” capabilities,this paper introduces it into multi-row DFLP by improving it.Finally,different algorithms are applied to the classical example for experimental tests.The results verify the effectiveness of mGA and BSA algorithm for solving multi-row DFLP problems.2)For optimizing the focused crawler retrieval technology,this paper proposes a focused crawler strategy based on ontology and simulated annealing algorithm(FCOSA).Firstly,FCOSA uses the two-stage filtering strategy based on global ontology and local ontology for the first time,and then combines the improved simulated annealing algorithm(ISA)to broaden the crawling path as much as possible and avoid the focused crawling into the local optimal search.Finally,with the topic of “rainstorm disasters”,the crawling strategy based on different optimization algorithms is realized.The experimental results show that the FCOSA algorithm is a very effective algorithm to optimize FC technology.