Evolutionary Techniques in Planning and Scheduling (EVOPS)

The EVOPS (EVOlutionary techniques for Planning and Scheduling) workshop will aim at providing an opportunity of interaction between researchers that share interests both on Planning and Scheduling and Evolutionary Computation Techniques. Since Planning and Scheduling problems are generally complex, constrained and multiobjective problems, the application of evolutionary algorithms, meta-heuristics and other soft computing techniques can be of help. The submission of works both on the use and on the application of evo techniques in P&S research is encouraged.

Online Proceedings (evops13-proceedings)

The EVOPS workshop is scheduled on the 11th of June in the A3 room at the Department of Computer, Control and Management Engineering (DIAG), University of Rome “SAPIENZA”.

14:30-14:40	Opening
14:40-15:20	M. Baioletti, R. Minciarelli, F. Paolucci, V. Poggioni Towards a new generation ACO-Based Planner
15:20-16:00	X. Li, R. Y. K. Fung Scheduling Single-Armed Cluster Tools with Time Window Constraints Using Differential Evolution Algorithm
16:00-16:30	Coffee Break
16:30-17:10	F. Siddiqui, P. Haslum Local Search in the Space of Valid Plans
17:10-17:50	M. Khouadjia, M. Schoenauer, V. Vidal, J. Dréo, P. Savéant Pareto-Based Multiobjective AI Planning
17:50	General Discussion

List of Accepted Papers

F. Siddiqui, P. Haslum
Local Search in the Space of Valid Plans
M. Khouadjia, M. Schoenauer, V. Vidal, J. Dréo, P. Savéant
Pareto-Based Multiobjective AI Planning
X. Li, R. Y. K. Fung
Scheduling Single-Armed Cluster Tools with Time Window Constraints Using Differential Evolution Algorithm
M. Baioletti, R. Minciarelli, F. Paolucci, V. Poggioni
Towards a new generation ACO-Based Planner

Call for papers

Topics and Objectives

Evolutionary computation is a well known set of computational techniques that are successfully applied in a wide range of scientific areas, including Artificial Intelligence, Operational Research, and Engineering.

Planning and Scheduling problems are generally complex, constrained and multiobjective problems. The application of evolutionary algorithms, meta-heuristics and other soft computing techniques can help Planning and Scheduling solvers both for the search problems and the optimization problems. These techniques are particularly well-suited for multiobjective optimization, and several algorithms are able to approximate (or even optimally compute) the Pareto front. While in the scheduling community the application of these techniques is quite popular, in the planning community they are still used in sporadic cases.

This event aims at favoring a cross fertilization promoting new ideas for models and applications for both the planning and scheduling community and the evolutionary community.

The workshop will be organized as a single day event (10 or 11 June, 2013) at ICAPS 2013 with a mixed approach that in part gives the opportunity to people to discuss their more recent (maybe ongoing) works and, on the other hand, provides a moment of effective exchange of opinions and experiences.

The first session will be composed of oral presentations of the accepted papers, while the second session will be an open discussion moderated by two invited speakers or members of the organizing committee, one from each community. These moderators will hopefully provide slightly contradictory brief surveys of the works presented during the previous session possibly relating them to the state of the art, and should stimulate the discussion.

This workshop will focus on evolutionary computation techniques for planning and scheduling (P&S) related, but not limited, to the following topics:

P&S models based on evolutionary and meta-heuristic approaches.
Indirect representations for evolutionary P&S
Hybridization of evolutionary and meta-heuristic techniques with other approaches for P&S
Real world applications in P&S.
Learning using evolutionary techniques for P&S
Analysis and characterization of benchmark problems
Multi-objective evolutionary and meta-heuristic P&S
Designing benchmarks for multi-objective P&S
P&S under uncertainty using evolutionary and meta-heuristic approaches
Parallel/distributed evolutionary algorithms and meta-heuristics for P&S
Evolutionary automated design of heuristics for P&S
Experience of applying evolutionary computation in P&S

Submissions

Papers must be prepared according to the AAAI style and instructions (see http://www.aaai.org/Publications/Author/author.php) and must be no more than ten (10) pages long, including figures and bibliography. Papers must be in PDF format and should be submitted via EasyChair conference system https://www.easychair.org/conferences/?conf=evops13.

Every submitted paper will be reviewed by at least two members of the Program Committee. Accepted papers will be included in the workshop notes.