scholarly journals An Approach to Temporal Planning and Scheduling in Domains with Predictable Exogenous Events

2006 ◽  
Vol 25 ◽  
pp. 187-231 ◽  
Author(s):  
A. Gerevini ◽  
A. Saetti ◽  
I. Serina
Keyword(s):  
Statistical Analysis ◽  
Time Windows ◽  
Temporal Reasoning ◽  
Temporal Constraints ◽  
Planning And Scheduling ◽  
Temporal Planning ◽  
Cpu Time ◽  
Planning Framework ◽  
Extra Difficulty ◽  
International Planning

The treatment of exogenous events in planning is practically important in many real-world domains where the preconditions of certain plan actions are affected by such events. In this paper we focus on planning in temporal domains with exogenous events that happen at known times, imposing the constraint that certain actions in the plan must be executed during some predefined time windows. When actions have durations, handling such temporal constraints adds an extra difficulty to planning. We propose an approach to planning in these domains which integrates constraint-based temporal reasoning into a graph-based planning framework using local search. Our techniques are implemented in a planner that took part in the 4th International Planning Competition (IPC-4). A statistical analysis of the results of IPC-4 demonstrates the effectiveness of our approach in terms of both CPU-time and plan quality. Additional experiments show the good performance of the temporal reasoning techniques integrated into our planner.

scholarly journals The 3rd International Planning Competition: Results and Analysis

2003 ◽  
Vol 20 ◽  
pp. 1-59 ◽  
Author(s):  
D. Long ◽  
M. Fox
Keyword(s):  
Statistical Analysis ◽  
Ai Planning ◽  
Relative Difficulty ◽  
Comparative Performance ◽  
Planning And Scheduling ◽  
International Conference ◽  
The Third ◽  
The Future ◽  
Problem Instances ◽  
International Planning

This paper reports the outcome of the third in the series of biennial international planning competitions, held in association with the International Conference on AI Planning and Scheduling (AIPS) in 2002. In addition to describing the domains, the planners and the objectives of the competition, the paper includes analysis of the results. The results are analysed from several perspectives, in order to address the questions of comparative performance between planners, comparative difficulty of domains, the degree of agreement between planners about the relative difficulty of individual problem instances and the question of how well planners scale relative to one another over increasingly difficult problems. The paper addresses these questions through statistical analysis of the raw results of the competition, in order to determine which results can be considered to be adequately supported by the data. The paper concludes with a discussion of some challenges for the future of the competition series.

scholarly journals On the Complexity and Expressiveness of Automated Planning Languages Supporting Temporal Reasoning

2017 ◽  
Author(s):  
Nicola Gigante
Keyword(s):  
Artificial Intelligence ◽  
Theoretical Study ◽  
Automated Planning ◽  
Temporal Reasoning ◽  
Temporal Constraints ◽  
Future Directions ◽  
Planning And Scheduling ◽  
Space Operations ◽  
Planning Problems ◽  
Over Time

Automated planning is an important area of Artificial Intelligence, which has been thoroughly developed in the last decades. In recent years, a significant amount of research has focused on planning languages and systems supporting temporal reasoning, recognizing its importance in modeling and solving real-world complex tasks. Many such languages are action-based, i.e. they model planning problems by specifying which actions can be executed at any given time to affect the environment. Timeline-based planning, a different paradigm originally introduced to support planning and scheduling of space operations, models planning domains as systems composed of a set of independent, but interacting, components, whose behavior over time, the timelines, is governed by a set of temporal constraints. A thorough theoretical study of timeline-based planning languages, and a rigorous comparison with action-based languages, are still missing. We outline recent results and future directions on this front.

A CSP-Based Approach for Temporal Constraints in Temporal Planning

2012 ◽  
Vol 35 (8) ◽  
pp. 1759
Author(s):  
Li-Hua WU ◽  
Ai-Xiang CHEN ◽  
Yun-Fei JIANG ◽  
Rui BIAN
Keyword(s):  
Temporal Constraints ◽  
Temporal Planning

scholarly journals The Design and Experimental Analysis of Algorithms for Temporal Reasoning

1996 ◽  
Vol 4 ◽  
pp. 1-18 ◽  
Author(s):  
P. Van Beek ◽  
D. W. Manchak
Keyword(s):  
Analysis Of Algorithms ◽  
Temporal Reasoning ◽  
Temporal Information ◽  
Search Problem ◽  
Planning And Scheduling ◽  
Backtracking Search ◽  
The Core ◽  
Reasoning System ◽  
Space Requirements ◽  
Experimental Analysis Of Algorithms

Many applications -- from planning and scheduling to problems in molecular biology -- rely heavily on a temporal reasoning component. In this paper, we discuss the design and empirical analysis of algorithms for a temporal reasoning system based on Allen's influential interval-based framework for representing temporal information. At the core of the system are algorithms for determining whether the temporal information is consistent, and, if so, finding one or more scenarios that are consistent with the temporal information. Two important algorithms for these tasks are a path consistency algorithm and a backtracking algorithm. For the path consistency algorithm, we develop techniques that can result in up to a ten-fold speedup over an already highly optimized implementation. For the backtracking algorithm, we develop variable and value ordering heuristics that are shown empirically to dramatically improve the performance of the algorithm. As well, we show that a previously suggested reformulation of the backtracking search problem can reduce the time and space requirements of the backtracking search. Taken together, the techniques we develop allow a temporal reasoning component to solve problems that are of practical size.

scholarly journals Planning Through Stochastic Local Search and Temporal Action Graphs in LPG

2003 ◽  
Vol 20 ◽  
pp. 239-290 ◽  
Author(s):  
A. Gerevini ◽  
A. Saetti ◽  
I. Serina
Keyword(s):  
Local Search ◽  
Search Method ◽  
Stochastic Local Search ◽  
Time System ◽  
Temporal Planning ◽  
The Core ◽  
International Planning ◽  
Domain Independent ◽  
Temporal Action

We present some techniques for planning in domains specified with the recent standard language PDDL2.1, supporting 'durative actions' and numerical quantities. These techniques are implemented in LPG, a domain-independent planner that took part in the 3rd International Planning Competition (IPC). LPG is an incremental, any time system producing multi-criteria quality plans. The core of the system is based on a stochastic local search method and on a graph-based representation called 'Temporal Action Graphs' (TA-graphs). This paper focuses on temporal planning, introducing TA-graphs and proposing some techniques to guide the search in LPG using this representation. The experimental results of the 3rd IPC, as well as further results presented in this paper, show that our techniques can be very effective. Often LPG outperforms all other fully-automated planners of the 3rd IPC in terms of speed to derive a solution, or quality of the solutions that can be produced.

scholarly journals Efficient Temporal Planning Using Metastates

2019 ◽  
Vol 33 ◽  
pp. 7554-7561 ◽  
Author(s):  
Amanda Coles ◽  
Andrew Coles ◽  
J. Christopher Beck
Keyword(s):  
State Space ◽  
State Of The Art ◽  
The State ◽  
The Other ◽  
Temporal Constraints ◽  
State Space Explosion ◽  
Temporal Planning ◽  
State Space Search ◽  
Temporal Inconsistency

When performing temporal planning as forward state-space search, effective state memoisation is challenging. Whereas in classical planning, two states are equal if they have the same facts and variable values, in temporal planning this is not the case: as the plans that led to the two states are subject to temporal constraints, one might be extendable into at temporally valid plan, while the other might not. In this paper, we present an approach for reducing the state space explosion that arises due to having to keep many copies of the same ‘classically’ equal state – states that are classically equal are aggregated into metastates, and these are separated lazily only in the case of temporal inconsistency. Our evaluation shows that this approach, implemented in OPTIC and compared to existing state-of-the-art memoisation techniques, improves performance across a range of temporal domains.

Planning with Concurrency, Time and Resources

2005 ◽  
pp. 259-295 ◽  
Author(s):  
Amedeo Cesta ◽  
Simone Fratini ◽  
Angelo Oddi
Keyword(s):  
Constraint Satisfaction ◽  
Resource Availability ◽  
Constraint Satisfaction Problem ◽  
Satellite System ◽  
Domain Model ◽  
Planning Problem ◽  
Planning And Scheduling ◽  
Planning Framework ◽  
Current Implementation ◽  
Domain Description

This chapter proposes to model a planning problem (e.g., the control of a satellite system) by identifying a set of relevant components in the domain (e.g., communication channels, on-board memory or batteries), which need to be controlled to obtain a desired temporal behavior. The domain model is enriched with the description of relevant constraints with respect to possible concurrency, temporal limits and scarce resource availability. The paper proposes a planning framework based on this view that relies on a formalization of the problem as a Constraint Satisfaction Problem (CSP) and defines an algorithmic template in which the integration of planning and scheduling is a fundamental feature. In addition, the paper describes the current implementation of a constraint-based planner called OMP that is grounded on these ideas and shows the role constraints have in this planner, both at domain description level and as a guide for problem solving.

scholarly journals Analysis of uncertainty in the surgical department: durations, requests and cancellations

2019 ◽  
Vol 43 (6) ◽  
pp. 706 ◽  
Author(s):  
Belinda Spratt ◽  
Erhan Kozan ◽  
Michael Sinnott
Keyword(s):  
Statistical Analysis ◽  
Total Duration ◽  
Analytical Techniques ◽  
Planning And Scheduling ◽  
Surgical Department ◽  
Modelling Uncertainty ◽  
Rate Dependent ◽  
Planning Staff ◽  
Log Normal ◽  
Surgical Duration

Objective Analytical techniques are being implemented with increasing frequency to improve the management of surgical departments and to ensure that decisions are well informed. Often these analytical techniques rely on the validity of underlying statistical assumptions, including those around choice of distribution when modelling uncertainty. The aim of the present study was to determine a set of suitable statistical distributions and provide recommendations to assist hospital planning staff, based on three full years of historical data. Methods Statistical analysis was performed to determine the most appropriate distributions and models in a variety of surgical contexts. Data from 2013 to 2015 were collected from the surgical department at a large Australian public hospital. Results A log-normal distribution approximation of the total duration of surgeries in an operating room is appropriate when considering probability of overtime. Surgical requests can be modelled as a Poisson process with rate dependent on urgency and day of the week. Individual cancellations could be modelled as Bernoulli trials, with the probability of patient-, staff- and resource-based cancellations provided herein. Conclusions The analysis presented herein can be used to ensure that assumptions surrounding planning and scheduling in the surgical department are valid. Understanding the stochasticity in the surgical department may result in the implementation of more realistic decision models. What is known about the topic? Many surgical departments rely on crude estimates and general intuition to predict surgical duration, surgical requests (both elective and non-elective) and cancellations. What does this paper add? This paper describes how statistical analysis can be performed to validate common assumptions surrounding surgical uncertainty. The paper also provides a set of recommended distributions and associated parameters that can be used to model uncertainty in a large public hospital’s surgical department. What are the implications for practitioners? The insights on surgical uncertainty provided here will prove valuable for administrative staff who want to incorporate uncertainty in their surgical planning and scheduling decisions.

Integrate Manufacturing Planning to Cloud Manufacturing Framework

2017 ◽  
Author(s):  
Xiangyun Li ◽  
Luping Zhang ◽  
Chunxia Yu
Keyword(s):  
Process Planning ◽  
Cloud Manufacturing ◽  
Concrete Case ◽  
Planning And Scheduling ◽  
Operational Mechanism ◽  
Manufacturing Planning ◽  
Sustainable Environment ◽  
Planning Framework ◽  
New Framework

We provide a cloud manufacturing based manufacturing planning framework for small and medium-sized enterprises. Manufacturing planning is conducted by separate units in the cloud instead of in corporations or manufacturing platforms. Disorders can be removed by the adoption of our newly-introduced units. To retain the workability of our new framework, three assumptions are imposed. A concrete case on process planning and scheduling is used for illustration of the necessity of our assumptions and operational mechanism of our design. Finally, a preliminary discuss on how intellect resources as well as small and medium-sized enterprises are involved to create a sustainable environment for small and medium-sized enterprises is placed.

Sign in / Sign up

Export Citation Format

Share Document