tag:crantastic.org,2005:/packages/FLSSSLatest activity for FLSSS2019-01-17T12:15:33Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/837452019-01-17T12:15:33Z2019-01-17T12:15:33Zcrantastic_production tagged FLSSS with Optimization<a href="/users/146">crantastic_production</a> <span class="action">tagged</span> <a href="/packages/FLSSS">FLSSS</a> with <a href="/task_views/Optimization">Optimization</a>crantastic_productiontag:crantastic.org,2005:TimelineEvent/834332019-01-11T12:41:15Z2019-01-11T12:41:15ZFLSSS was upgraded to version 8.5.2<a href="/packages/FLSSS">FLSSS</a> was <span class="action">upgraded</span> to version <a href="/packages/FLSSS/versions/79399">8.5.2</a><br /><h3>Package description:</h3><p>Specialized solvers for combinatorial optimization problems in the Subset Sum family. These solvers differ from the mainstream in the options of (i) restricting subset size, (ii) bounding subset elements, (iii) mining real-value sets with predefined subset sum errors, and (iv) finding one or more subsets in limited time. A novel algorithm for mining the one-dimensional Subset Sum induced algorithms for the multi-Subset Sum and the multidimensional Subset Sum. The latter decomposes the problem in a novel approach, and the multi-threaded framework offers exact algorithms to the multidimensional Knapsack and the Generalized Assignment problems. Package updates include (a) renewed implementation of the multi-Subset Sum, multidimensional Knapsack and Generalized Assignment solvers; (b) availability of bounding solution space in the multidimensional Subset Sum; (c) fundamental data structure and architectural changes for enhanced cache locality and better chance of SIMD vectorization; (d) an option of mapping real-domain problems to the integer domain with user-controlled precision loss, and those integers are further zipped non-uniformly in 64-bit buffers. Arithmetic on compressed integers is done by bit-manipulation and the design has virtually zero speed lag relative to normal integers arithmetic. The consequent reduction in dimensionality may yield substantial acceleration. Compilation with g++ '-Ofast' is recommended. See package vignette (<arXiv:1612.04484v3>) for details. Functions prefixed with 'aux' (auxiliary) are or will be implementations of existing foundational or cutting-edge algorithms for solving optimization problems of interest.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/832752019-01-08T09:01:19Z2019-01-08T09:01:19ZFLSSS was upgraded to version 8.3<a href="/packages/FLSSS">FLSSS</a> was <span class="action">upgraded</span> to version <a href="/packages/FLSSS/versions/79242">8.3</a><br /><h3>Package description:</h3><p>Specialized solvers for combinatorial optimization problems in the Subset Sum family. These solvers differ from the mainstream in the options of (i) restricting subset size, (ii) bounding subset elements, (iii) mining real-value sets with predefined subset sum errors, and (iv) finding one or more subsets in limited time. A novel algorithm for mining the one-dimensional Subset Sum induced algorithms for the multi-Subset Sum and the multidimensional Subset Sum. The latter decomposes the problem in a novel approach, and the multi-threaded framework offers exact algorithms to the multidimensional Knapsack and the Generalized Assignment problems. Package updates include (a) renewed implementation of the multi-Subset Sum, multidimensional Knapsack and Generalized Assignment solvers; (b) availability of bounding solution space in the multidimensional Subset Sum; (c) fundamental data structure and architectural changes for enhanced cache locality and better chance of SIMD vectorization; (d) an option of mapping real-domain problems to the integer domain with user-controlled precision loss, and those integers are further zipped non-uniformly in 64-bit buffers. Arithmetic on compressed integers is done by bit-manipulation and the design has virtually zero speed lag relative to normal integers arithmetic. The consequent reduction in dimensionality may yield substantial acceleration. Compilation with g++ '-Ofast' is recommended. See package vignette (<arXiv:1612.04484v3>) for details. Functions prefixed with 'aux' (auxiliary) are or will be implementations of existing foundational or cutting-edge algorithms for solving optimization problems of interest.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/820092018-11-22T17:41:18Z2018-11-22T17:41:18ZFLSSS was upgraded to version 7.7<a href="/packages/FLSSS">FLSSS</a> was <span class="action">upgraded</span> to version <a href="/packages/FLSSS/versions/78034">7.7</a><br /><h3>Package description:</h3><p>Specialized solvers for combinatorial optimization problems in the Subset Sum family. These solvers differ from the mainstream in the options of (i) restricting subset size, (ii) bounding subset elements, (iii) mining real-value sets with predefined subset sum errors, and (iv) finding one or more subsets in limited time. A novel algorithm for mining the one-dimensional Subset Sum induced algorithms for the multi-Subset Sum and the multidimensional Subset Sum. The latter decomposes the problem in a novel approach, and the multi-threaded framework offers exact algorithms to the multidimensional Knapsack and the Generalized Assignment problems. Package updates include (a) renewed implementation of the multi-Subset Sum, multidimensional Knapsack and Generalized Assignment solvers; (b) availability of bounding solution space in the multidimensional Subset Sum; (c) fundamental data structure and architectural changes for enhanced cache locality and better chance of SIMD vectorization; (d) an option of mapping real-domain problems to the integer domain with user-controlled precision loss, and those integers are further zipped non-uniformly in 64-bit buffers. Arithmetic on compressed integers is done by bit-manipulation and the design has virtually zero speed lag relative to normal integers arithmetic. The consequent reduction in dimensionality could yield substantial acceleration. Aggressive compiling, e.g. g++ '-Ofast', may speed up mining on some platforms. See package vignette (<arXiv:1612.04484v3>) for more details.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/790532018-08-28T14:21:03Z2018-08-28T14:21:03ZFLSSS was upgraded to version 7.6<a href="/packages/FLSSS">FLSSS</a> was <span class="action">upgraded</span> to version <a href="/packages/FLSSS/versions/75396">7.6</a><br /><h3>Package description:</h3><p>Specialized solvers for combinatorial optimization problems in the Subset Sum family. These solvers differ from the mainstream in the options of (i) subset size restriction, (ii) bounds on the subset elements, (iii) mining real-value sets with predefined subset sum errors, and (iv) finding one or more subsets in limited time. A novel algorithm for mining the one-dimensional Subset Sum induced algorithms for the multi-Subset Sum and the multidimensional Subset Sum. The latter is creatively scheduled in a multi-threaded environment, and the framework offers strong applications to the multidimensional Knapsack and the Generalized Assignment problems. Package updates include (a) renewed implementation of the multi-Subset Sum, multidimensional Knapsack and Generalized Assignment solvers; (b) availability of bounding solution space in the multidimensional Subset Sum; (c) fundamental data structure and architectural changes for enhanced cache locality and better chance of SIMD vectorization; (d) an option of mapping real-domain problems to the integer domain with controlled precision loss, and those integers are further zipped non-uniformly in 64-bit buffers. Arithmetic on compressed integers has a novel design with virtually zero speed lag relative to that on normal integers, and the consequent reduction in dimensionality often leads to substantial acceleration. Compilation with aggressive optimization, e.g. g++ '-Ofast', may speed up mining on some platforms. Package documentation (<arXiv:1612.04484v2>) is outdated as the time of writing.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/789992018-08-26T07:01:12Z2018-08-26T07:01:12ZFLSSS was upgraded to version 7.5<a href="/packages/FLSSS">FLSSS</a> was <span class="action">upgraded</span> to version <a href="/packages/FLSSS/versions/75342">7.5</a><br /><h3>Package description:</h3><p>Specialized solvers for combinatorial optimization problems in the Subset Sum family. These solvers differ from the mainstream in the options of (i) subset size restriction, (ii) bounds on the subset elements, (iii) mining real-value sets with predefined subset sum errors, and (iv) finding one or more subsets in limited time. A novel algorithm for mining the one-dimensional Subset Sum induced algorithms for the multi-Subset Sum and the multidimensional Subset Sum. The latter is creatively decomposed and scheduled in a multi-threaded environment, and the framework offers strong applications to the multidimensional Knapsack and the Generalized Assignment problems. Package updates include (a) renewed implementation of the multi-Subset Sum, multidimensional Knapsack and Generalized Assignment solvers; (b) availability of bounding solution space in the multidimensional Subset Sum; (c) fundamental data structure and architectural changes for enhanced cache locality and better chance of SIMD vectorization; (d) an option of mapping real-domain problems to the integer domain with controlled precision loss, and those integers are further zipped in 64-bit buffers for SWAR and dimension reduction that often lead to substantial acceleration. See the package documentation for compressed integer arithmetic. Compilation with aggressive optimization, e.g. g++ '-Ofast', might speed up mining on some architectures. Package documentation (<arXiv:1612.04484v2>) is outdated as the time of writing.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/576792016-12-14T07:20:48Z2016-12-14T07:20:48ZFLSSS was upgraded to version 5.2<a href="/packages/FLSSS">FLSSS</a> was <span class="action">upgraded</span> to version <a href="/packages/FLSSS/versions/55230">5.2</a><br /><h3>Package description:</h3><p>A novel algorithm for solving the subset sum problem with bounded error in multidimensional real domain and its application to the general-purpose knapsack problem.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/576592016-12-13T19:00:52Z2016-12-13T19:00:52ZFLSSS was upgraded to version 5.1<a href="/packages/FLSSS">FLSSS</a> was <span class="action">upgraded</span> to version <a href="/packages/FLSSS/versions/55210">5.1</a><br /><h3>Package description:</h3><p>A novel algorithm for solving the subset sum problem with bounded error in multidimensional real domain and its application to the general-purpose knapsack problem.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/505332016-04-20T07:00:41Z2016-04-20T07:00:41ZFLSSS was upgraded to version 5.0.1<a href="/packages/FLSSS">FLSSS</a> was <span class="action">upgraded</span> to version <a href="/packages/FLSSS/versions/48849">5.0.1</a><br /><h3>Package description:</h3><p>A novel algorithm for solving the fixed size Subset Sum Problem with bounded error in multidimensional real domain.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/361622014-05-29T08:30:55Z2014-05-29T08:30:55ZFLSSS was released<a href="/packages/FLSSS">FLSSS</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>Specialized solvers for combinatorial optimization problems in the Subset Sum family. These solvers differ from the mainstream in the options of (i) restricting subset size, (ii) bounding subset elements, (iii) mining real-value sets with predefined subset sum errors, and (iv) finding one or more subsets in limited time. A novel algorithm for mining the one-dimensional Subset Sum induced algorithms for the multi-Subset Sum and the multidimensional Subset Sum. The latter decomposes the problem in a novel approach, and the multi-threaded framework offers exact algorithms to the multidimensional Knapsack and the Generalized Assignment problems. Package updates include (a) renewed implementation of the multi-Subset Sum, multidimensional Knapsack and Generalized Assignment solvers; (b) availability of bounding solution space in the multidimensional Subset Sum; (c) fundamental data structure and architectural changes for enhanced cache locality and better chance of SIMD vectorization; (d) an option of mapping real-domain problems to the integer domain with user-controlled precision loss, and those integers are further zipped non-uniformly in 64-bit buffers. Arithmetic on compressed integers is done by bit-manipulation and the design has virtually zero speed lag relative to normal integers arithmetic. The consequent reduction in dimensionality may yield substantial acceleration. Compilation with g++ '-Ofast' is recommended. See package vignette (<arXiv:1612.04484v3>) for details. Functions prefixed with 'aux' (auxiliary) are or will be implementations of existing foundational or cutting-edge algorithms for solving optimization problems of interest.</p>crantastic.org