Benchmark Results for Bookshelf Organization Problem as Mixed Integer Nonlinear Program with Mode Switch and Collision Avoidance
Mixed integer convex and nonlinear programs, MICP and MINLP, are expressive but require long solving times. Recent work that combines data-driven methods on solver heuristics has shown potential to overcome this issue allowing for applications on larger scale practical problems. To solve mixed-integ...
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| creator | Lin, Xuan Fernandez, Gabriel I Hong, Dennis W |
| description | Mixed integer convex and nonlinear programs, MICP and MINLP, are expressive
but require long solving times. Recent work that combines data-driven methods
on solver heuristics has shown potential to overcome this issue allowing for
applications on larger scale practical problems. To solve mixed-integer
bilinear programs online with data-driven methods, several formulations exist
including mathematical programming with complementary constraints (MPCC),
mixed-integer programming (MIP). In this work, we benchmark the performances of
those data-driven schemes on a bookshelf organization problem that has discrete
mode switch and collision avoidance constraints. The success rate, optimal cost
and solving time are compared along with non-data-driven methods. Our proposed
methods are demonstrated as a high level planner for a robotic arm for the
bookshelf problem. |
| doi_str_mv | 10.48550/arxiv.2208.13158 |
| format | Article |
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but require long solving times. Recent work that combines data-driven methods
on solver heuristics has shown potential to overcome this issue allowing for
applications on larger scale practical problems. To solve mixed-integer
bilinear programs online with data-driven methods, several formulations exist
including mathematical programming with complementary constraints (MPCC),
mixed-integer programming (MIP). In this work, we benchmark the performances of
those data-driven schemes on a bookshelf organization problem that has discrete
mode switch and collision avoidance constraints. The success rate, optimal cost
and solving time are compared along with non-data-driven methods. Our proposed
methods are demonstrated as a high level planner for a robotic arm for the
bookshelf problem.</description><identifier>DOI: 10.48550/arxiv.2208.13158</identifier><language>eng</language><subject>Computer Science - Robotics ; Mathematics - Optimization and Control</subject><creationdate>2022-08</creationdate><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2208.13158$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2208.13158$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Lin, Xuan</creatorcontrib><creatorcontrib>Fernandez, Gabriel I</creatorcontrib><creatorcontrib>Hong, Dennis W</creatorcontrib><title>Benchmark Results for Bookshelf Organization Problem as Mixed Integer Nonlinear Program with Mode Switch and Collision Avoidance</title><description>Mixed integer convex and nonlinear programs, MICP and MINLP, are expressive
but require long solving times. Recent work that combines data-driven methods
on solver heuristics has shown potential to overcome this issue allowing for
applications on larger scale practical problems. To solve mixed-integer
bilinear programs online with data-driven methods, several formulations exist
including mathematical programming with complementary constraints (MPCC),
mixed-integer programming (MIP). In this work, we benchmark the performances of
those data-driven schemes on a bookshelf organization problem that has discrete
mode switch and collision avoidance constraints. The success rate, optimal cost
and solving time are compared along with non-data-driven methods. Our proposed
methods are demonstrated as a high level planner for a robotic arm for the
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but require long solving times. Recent work that combines data-driven methods
on solver heuristics has shown potential to overcome this issue allowing for
applications on larger scale practical problems. To solve mixed-integer
bilinear programs online with data-driven methods, several formulations exist
including mathematical programming with complementary constraints (MPCC),
mixed-integer programming (MIP). In this work, we benchmark the performances of
those data-driven schemes on a bookshelf organization problem that has discrete
mode switch and collision avoidance constraints. The success rate, optimal cost
and solving time are compared along with non-data-driven methods. Our proposed
methods are demonstrated as a high level planner for a robotic arm for the
bookshelf problem.</abstract><doi>10.48550/arxiv.2208.13158</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Robotics Mathematics - Optimization and Control |
| title | Benchmark Results for Bookshelf Organization Problem as Mixed Integer Nonlinear Program with Mode Switch and Collision Avoidance |
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