IH
I.K. Hanou
info
Please Note
<p>This page displays the records of the person named above and is not linked to a unique person identifier. This record may need to be merged to a profile.</p>
2 records found
1
Comparing planners for rail planning in PDDL
How multiple shunting yard layouts can be created in PDDL to replicate real-world scenarios
This paper explored the usage of the Planning Domain Definition Language in the Train Unit Shunting Problem or TUSP, an NP-hard problem that occurs in train storage. This paper focuses on the evaluation and improvement of existing planners to solve TUSP with multiple shunting yard layouts, as well as an appropriate domain with it. Starting with the implementation of multiple shunting yards in the domain, by connecting train tracks in problem instances. Followed by the evaluation of the planners, where planners are evaluated on speed, plan cost and solvability. Among the evaluated planners, the Team4 planner from the International Planning Competition 2018 demonstrates exceptional performance by successfully solving all problem instances and having the highest speed overall. Finally, the Team4 planner was optimised, specifically by improving the domain for Last In First Out, LIFO, tracks, since it encountered difficulties when solving problems that contained these tracks. The tracks were given new predicates and actions, resulting in much higher speeds for problems that consisted of LIFO tracks. Results suggest that a suitable planner has been improved for solving TUSP with multiple shunting yard layouts and that planners are indeed capable of handling the complexities that come along with multiple shunting yard layouts.
...
This paper explored the usage of the Planning Domain Definition Language in the Train Unit Shunting Problem or TUSP, an NP-hard problem that occurs in train storage. This paper focuses on the evaluation and improvement of existing planners to solve TUSP with multiple shunting yard layouts, as well as an appropriate domain with it. Starting with the implementation of multiple shunting yards in the domain, by connecting train tracks in problem instances. Followed by the evaluation of the planners, where planners are evaluated on speed, plan cost and solvability. Among the evaluated planners, the Team4 planner from the International Planning Competition 2018 demonstrates exceptional performance by successfully solving all problem instances and having the highest speed overall. Finally, the Team4 planner was optimised, specifically by improving the domain for Last In First Out, LIFO, tracks, since it encountered difficulties when solving problems that contained these tracks. The tracks were given new predicates and actions, resulting in much higher speeds for problems that consisted of LIFO tracks. Results suggest that a suitable planner has been improved for solving TUSP with multiple shunting yard layouts and that planners are indeed capable of handling the complexities that come along with multiple shunting yard layouts.
Optimizing the PDDL domain of TUSP to improve planner performance
Modifying the domain to improve planner execution time, plan quality, and problem solvability
It is possible to improve the performance of planners by modifying the PDDL domain of a problem. The goal of this research is to implement this to the domain of the Train Unit Shunting Problem (TUSP). The research question we attempt to answer is: To what extent can we improve planner performance by optimizing the PDDL domain of TUSP? The main contributions of this research are: a formalization of the TUSP and its constraints in PDDL terminology, a comprehensive evaluation of the performance of planners on the PDDL domain of TUSP, provide general approaches and techniques that can be used to optimize a PDDL domain, and provide insights into the relationship between the performance of planners and PDDL domain properties. To answer the research question, we measure the performance of the planners in terms of execution time, plan quality, and problem solvability. We modified the domain by combining actions such that the number of computations is decreased and by introducing action costs. With these modifications, we found a decrease in planner execution time and an increase in plan quality. We found no difference in problem solvability. Therefore, we can conclude that we can indeed improve the performance of planners by implementing these modifications to the domain of TUSP.
...
It is possible to improve the performance of planners by modifying the PDDL domain of a problem. The goal of this research is to implement this to the domain of the Train Unit Shunting Problem (TUSP). The research question we attempt to answer is: To what extent can we improve planner performance by optimizing the PDDL domain of TUSP? The main contributions of this research are: a formalization of the TUSP and its constraints in PDDL terminology, a comprehensive evaluation of the performance of planners on the PDDL domain of TUSP, provide general approaches and techniques that can be used to optimize a PDDL domain, and provide insights into the relationship between the performance of planners and PDDL domain properties. To answer the research question, we measure the performance of the planners in terms of execution time, plan quality, and problem solvability. We modified the domain by combining actions such that the number of computations is decreased and by introducing action costs. With these modifications, we found a decrease in planner execution time and an increase in plan quality. We found no difference in problem solvability. Therefore, we can conclude that we can indeed improve the performance of planners by implementing these modifications to the domain of TUSP.