Constraint satisfaction and optimization for space station short-term mission planning based on an iterative conflict-repair method

Bu, Hui-Jiao; Zhang, Jin; Luo, Yuling

doi:10.1080/0305215x.2015.1137566

Cited by 7 publications

(3 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…ThistechniqueisprovedtheirefficiencytosolvemanycasestudiesonCSOPs. (Bu,Zhang,&Luo, 2016)treatedtheoptimizationofspacestationshort-termmissionplanning(STMP)problem.The STMP problem complicated planning problem that characterized by a multi-constraint. Authors developedamissionplanningmodelbasedonconstraintsatisfaction,presentedwithaninteractive conflict-repairmethod.Theyusedthebacktrackingbasedonresolvingstrategiesthatareproposedto satisfycomplexconstraints.Then,theyappliedageneticalgorithmtooptimizetheSTMPproblem.…”

Section: Planning Transportation Problem Solved As Csop: Literature R...mentioning

confidence: 99%

Multi-Layer Distributed Constraint Satisfaction for Multi-criteria Optimization Problem

Mnif

Bouamama

2020

International Journal of Applied Metaheuristic Computing

View full text Add to dashboard Cite

This article introduces a new approach to solve the multimodal transportation network planning problem (MTNP). In this problem, the commodities must be transported from an international network by at least two different transport modes. The main purpose is to identify the best multimodal transportation strategy. The present contribution focuses on efficient optimization methods to solve MTNP. This includes the assignment and the scheduling problems. The authors split the MTNP into layered. Each layer is presented by an agent. These agents interact, collaborate, and communicate together to solve the problem. This article defines MTNP as a distributed constraint satisfaction multi-criteria optimization problem (DCSMOP). This latter is a description of the constraint optimization problem (COP), where variables and constraints are distributed among a set of agents. Each agent can interact with other agents to share constraints and to distribute complementary tasks. Experimental results are the proof of this work efficiently.

show abstract

Section: Planning Transportation Problem Solved As Csop: Literature R...mentioning

confidence: 99%

Multi-Layer Distributed Constraint Satisfaction for Multi-criteria Optimization Problem

Mnif

Bouamama

2020

International Journal of Applied Metaheuristic Computing

View full text Add to dashboard Cite

show abstract

“…In the last several years, while research has been conducted that focuses on enabling increased flight crew autonomy for future LDEMs, there is comparatively little within the domain of autonomy in mission activity scheduling. Some research has emphasized solutions that support scheduling efficiency, such as decision support systems (e.g., Mishra et al, ., 2019) and algorithms for increased scheduling efficiency (e.g., Bu et al, 2016). Our previous research has centered around the design and usability of scheduling tools for self-scheduling in analog environments (Marquez et al, 2017, 2019) and in spaceflight (Marquez, Hillenius, Healy & Silva-Martinez, 2019).…”

Section: Introductionmentioning

confidence: 99%

Human Performance of Novice Schedulers for Complex Spaceflight Operations Timelines

et al. 2021

View full text Add to dashboard Cite

Objective Investigate the effects of scheduling task complexity on human performance for novice schedulers creating spaceflight timelines. Background Future astronauts will be expected to self-schedule, yet will not be experts in creating timelines that meet the complex constraints inherent to spaceflight operations. Method Conducted a within-subjects experiment to evaluate scheduling task performance in terms of scheduling efficiency, effectiveness, workload, and situation awareness while manipulating scheduling task complexity according to the number of constraints and type of constraints. Results Each participant ( n = 15) completed a set of scheduling problems. Results showed main effects of the number of constraints and type of constraint on efficiency, effectiveness, and workload. Significant interactions were observed in situation awareness and workload for certain types of constraints. Results also suggest that a lower number of constraints may be manageable by novice schedulers when compared to scheduling activities without constraints. Conclusion Results suggest that novice schedulers' performance decreases with a high number of constraints, and future scheduling aids may need to target a specific type of constraint. Application Knowledge on the effect of scheduling task complexity will help design scheduling systems that will enable self-scheduling for future astronauts. It will also inform other domains that conduct complex scheduling, such as nursing and manufacturing.

show abstract

“…There has been made greatly advances in planning community due to the application of constraint satisfaction techniques (Alur, Henzinger and Vardi, 2015;Günay and Yolum, 2013) in recent years. Constraint-programmed planners (Bu, Zhang and Luo, 2016;Lozano-Perez and Kaelbling, 2014) code a planning problem into a constraint satisfaction problem (CSP) and then apply powerful CSP algorithm to inference and prune off. Clearly there are two benefits for this translation: one is the researchers can directly use the mature algorithms in CSP community with a constraint-programmed planner, and the second is AI planning and CSP stress on the different control theories respectively: planning emphasizes on search (Kautz and Selman, 1999) while CSP on inference (Veksler and Strichman, 2016).…”

Section: Introductionmentioning

confidence: 99%

An Action Guided Constraint Satisfaction Technique for Planning Problem

Jiang

Cui

et al. 2016

International Journal of Software Science and Computational Intelligence

View full text Add to dashboard Cite

This paper presents an action guided constraint satisfaction technique for planning problem. Different from the standard algorithms which are almost domain independence and cannot reflect the characteristics of the planning progress, this paper discusses how the action rules in planning act in constraint satisfaction problems. Based on the conclusion, an action directed constraint is proposed to guide the variable selected procedure in constraint satisfaction problems. Through theoretical analysis, this technique is prior an order of magnitude in variable select procedure over the ordinary heuristic technique and can be used in constraint-programmed planning problem generally. With the simulation experiments it shows that the algorithm with action guided constraint can effectively reduce the number of constraint checks during the planning procedure and has a better performance on total running time over the standard version.

show abstract

Constraint satisfaction and optimization for space station short-term mission planning based on an iterative conflict-repair method

Cited by 7 publications

References 18 publications

Multi-Layer Distributed Constraint Satisfaction for Multi-criteria Optimization Problem

Multi-Layer Distributed Constraint Satisfaction for Multi-criteria Optimization Problem

Human Performance of Novice Schedulers for Complex Spaceflight Operations Timelines

An Action Guided Constraint Satisfaction Technique for Planning Problem

Contact Info

Product

Resources

About