{"title":"Very Large-Scale Integration Floor Planning on FIR and Lattice Filters Design With Multi-Objective Hybrid Optimization","authors":"Pushpalatha Pondreti, Babulu Kaparapu","doi":"10.4018/ijsir.321237","DOIUrl":null,"url":null,"abstract":"Floor planning is indeed an obvious design process in VLSI physical layout since it specifies the dimensions, structure, as well as positions of components upon the chip; in addition, information regarding the overarching silicon area, interlinks, and latency is also provided. VLSI floor planning is an NP-hard issue as the floor plan representations are a crucial component in this process. The intricacy, as well as solution space of the floor plan layout, is influenced by the floorplan visualizations. To tackle the VLSI floor plan challenge, numerous researchers have developed numerous meta-heuristic optimization techniques. The main objective of this work presents a novel multi-objective hybrid optimization method for solving the floor plan optimization issue. Standard DOX and ALO are conceptually combined in the proposed hybrid optimization referred to as Dingo Updated Ant Lion Optimization (DUALO) model. The multi-objectives like wire length, area, and penalty function are taken into consideration.","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":"1 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Swarm Intelligence Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijsir.321237","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Floor planning is indeed an obvious design process in VLSI physical layout since it specifies the dimensions, structure, as well as positions of components upon the chip; in addition, information regarding the overarching silicon area, interlinks, and latency is also provided. VLSI floor planning is an NP-hard issue as the floor plan representations are a crucial component in this process. The intricacy, as well as solution space of the floor plan layout, is influenced by the floorplan visualizations. To tackle the VLSI floor plan challenge, numerous researchers have developed numerous meta-heuristic optimization techniques. The main objective of this work presents a novel multi-objective hybrid optimization method for solving the floor plan optimization issue. Standard DOX and ALO are conceptually combined in the proposed hybrid optimization referred to as Dingo Updated Ant Lion Optimization (DUALO) model. The multi-objectives like wire length, area, and penalty function are taken into consideration.
期刊介绍:
The mission of the International Journal of Swarm Intelligence Research (IJSIR) is to become a leading international and well-referred journal in swarm intelligence, nature-inspired optimization algorithms, and their applications. This journal publishes original and previously unpublished articles including research papers, survey papers, and application papers, to serve as a platform for facilitating and enhancing the information shared among researchers in swarm intelligence research areas ranging from algorithm developments to real-world applications.