FLSSS: A Novel Algorithmic Framework for Combinatorial Optimization\n Problems in the Subset Sum Family

2016/12/13 by Charlie Wusuo Liu, Liu, Charlie Wusuo
Computer Science · #Algorithms and Data Compression #Data Management and Algorithms #Data Mining Algorithms and Applications #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences

paper · pdf · doi:10.48550/arxiv.1612.04484

openalex publication_date 2016/12/13 · openalex created_date 2022/09/02 · openalex updated_date 2026/07/28

Abstract

This article details the algorithmics in FLSSS, an R package for solving\nvarious subset sum problems. The fundamental algorithm engages the problem via\ncombinatorial space compression adaptive to constraints, relaxations and\nvariations that are often crucial for data analytics in practice. Such\nadaptation conversely enables the compression algorithm to drain every bit of\ninformation a sorted superset could bring for rapid convergence.\nMultidimensional extension follows a novel decomposition of the problem and is\nfriendly to multithreading. Data structures supporting the algorithms have\ntrivial space complexity. The framework offers exact algorithms for the\nmultidimensional knapsack problem and the generalized assignment problem.\n

Citations

• The Proof and Measurement of Association between Two Things

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