Applications of Answer Set Programming in Phylogenetic Systematics

Erdem, Esra

doi:10.1007/978-3-642-20832-4_26

Cited by 11 publications

(4 citation statements)

References 25 publications

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“…ASP has been used to solve combinatorial knowledge-based problems in many different areas. Among the most outstanding applications are the decision-making system of a spacecraft [10], planning for the generation of equipment in a shipyard [11], phylogenetic systems [12], autonomous vehicles in Car Assembly [13], and re-scheduling for an operating room [14].…”

Section: Introductionmentioning

confidence: 99%

Optimal Scheduling for Automated Wetetch Stations with One Robot in Semiconductor Manufacturing via Constraint Answer Set Programming

García-Mata,

Burtseva,

Werner

2024

Preprint

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Scheduling and optimization have a central place in the research area of computing because it is increasingly important to achieve fully automated production processes to adjust manufacturing systems to the requirements of Industry 4.0. In this paper, we demonstrate how an automated wet-etch scheduling problem for a semiconductor industry can be solved by constraint answer set programming (CASP) and, its solver called clingcon. The considered scheduling problem includes a robot for lot transfers between the baths. CASP is a hybrid approach in automated reasoning that combines different research areas such as answer set programming, Constraint Processing and Satisfiability Modulo Theories. For a long time, exact methods such as constraint programming have displayed difficulties in solving real large-scale problem instances. Currently, the performance of state-of-the-art constrains solvers is comparatively better than a decade ago, and some complex combinatorial problems can be optimally solved. These theoretical and technical achievements open new horizons for declarative programming applications such as logistics. A successful solution to this problem is achieved and we found that in most cases tested, CASP is faster and obtains in most cases similar makespan values than solutions based on mixed integer linear programming and constraint paradigms.

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Section: Introductionmentioning

confidence: 99%

Optimal Scheduling for Automated Wetetch Stations with One Robot in Semiconductor Manufacturing via Constraint Answer Set Programming

García-Mata,

Burtseva,

Werner

2024

Preprint

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“…ASP has been used to solve combinatorial knowledge-based problems in many different areas. Among the most outstanding applications are the decision-making system of a spacecraft [15], planning for the generation of equipment in a shipyard [16], phylogenetic systems [17], autonomous vehicles in Car Assembly [18], rescheduling for an operating room [19], diagnosis [20], and planning [21].…”

Section: Introductionmentioning

confidence: 99%

Scheduling of Automated Wet-Etch Stations with One Robot in Semiconductor Manufacturing via Constraint Answer Set Programming

García-Mata,

Burtseva,

Werner

2024

Processes

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Scheduling and optimization have a central place in the research area of computing because it is increasingly important to achieve fully automated production processes to adjust manufacturing systems to the requirements of Industry 4.0. In this paper, we demonstrate how an automated wet-etch scheduling problem for the semiconductor industry can be solved by constraint answer set programming (CASP) and its solver called clingcon. A successful solution to this problem is achieved, and we found that for all tested problems, CASP is faster and obtains smaller makespan values for seven of the eight problems tested than the solutions based on mixed integer linear programming and constraint paradigms. The considered scheduling problem includes a robot for lot transfers between baths. CASP is a hybrid approach in automated reasoning that combines different research areas such as answer set programming, constraint processing, and Satisfiability Modulo Theories. For a long time, exact methods such as constraint programming have displayed difficulties in solving real large-scale problem instances. Currently, the performance of state-of-the-art constraint solvers is comparatively better than a decade ago, and some complex combinatorial problems can be better solved. These theoretical and technical achievements open new horizons for declarative programming applications such as logistics.

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“…Thanks to its high readability and expressiveness, and the availability of efficient solvers, many ASP-based applications have been presented in the literature (Erdem, Gelfond, & Leone, 2016), in several areas ranging from Artificial Intelligence Baral & Gelfond, 2000;Baral & Uyan, 2001;Brewka, Niemelä, & Syrjänen, 2002;Garro, Palopoli, & Ricca, 2006;Nogueira, Balduccini, Gelfond, Watson, & Barry, 2001) to Knowledge Management (Baral, 2003;Bardadym, 1996), Databases (Bertossi, Hunter, & Schaub, 2005;Bravo & Bertossi, 2003;Leone, Gottlob, Rosati, Eiter, Faber, Fink, Greco, Ianni, Kałka, Lembo, Lenzerini, Lio, Nowicki, Ruzzi, Staniszkis, & Terracina, 2005;Manna, Ricca, & Terracina, 2013, Phylogeny (Erdem, 2011;Koponen, Oikarinen, Janhunen, & Säilä, 2015), Bio-informatics (Dworschak, Grell, Nikiforova, Schaub, & Selbig, 2008;Gebser, Schaub, Thiele, & Veber, 2011), and industrial settings (Aschinger, Drescher, Friedrich, Gottlob, Jeavons, Ryabokon, & Thorstensen, • We describe the refined benchmark selection process applied for the first time, which consists of a classification of available instances based on empirical hardness along with a balanced selection accomplished by means of ASP.…”

Section: Introductionmentioning

confidence: 99%

The Sixth Answer Set Programming Competition

Gebser¹,

Maratea²,

Ricca³

2017

jair

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Answer Set Programming (ASP) is a well-known paradigm of declarative programming with roots in logic programming and non-monotonic reasoning. Similar to other closely related problemsolving technologies, such as SAT/SMT, QBF, Planning and Scheduling, advancements in ASP solving are assessed in competition events. In this paper, we report about the design and results of the Sixth ASP Competition, which was jointly organized by the University of Calabria (Italy), Aalto University (Finland), and the University of Genoa (Italy), in affiliation with the 13th International Conference on Logic Programming and Non-Monotonic Reasoning. This edition maintained some of the design decisions introduced in 2014, e.g., the conception of sub-tracks, the scoring scheme, and the adherence to a fixed modeling language in order to push the adoption of the ASP-Core-2 standard. On the other hand, it featured also some novelties, like a benchmark selection stage classifying instances according to their empirical hardness, and a "Marathon" track where the topperforming systems are given more time for solving hard benchmarks.

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Applications of Answer Set Programming in Phylogenetic Systematics

Cited by 11 publications

References 25 publications

Optimal Scheduling for Automated Wetetch Stations with One Robot in Semiconductor Manufacturing via Constraint Answer Set Programming

Optimal Scheduling for Automated Wetetch Stations with One Robot in Semiconductor Manufacturing via Constraint Answer Set Programming

Scheduling of Automated Wet-Etch Stations with One Robot in Semiconductor Manufacturing via Constraint Answer Set Programming

The Sixth Answer Set Programming Competition

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