March 21, 2019: Prize money - the winner(s) of the competition will receive a cash prize of AUD 400 (sponsored by Markus Wagner)
March 18, 2019: Leaderboard was created. From now on every submission will be reflected.
Feb 20, 2019: We are happy to announce the competition started. Submissions will be accepted until June 30, 2019, Midnight, UTC-12.
The Genetic and Evolutionary Computation Conference (GECCO) presents the latest high-quality results in genetic and evolutionary computation since 1999. Topics include: genetic algorithms, genetic programming, ant colony optimization and swarm intelligence, complex systems (artificial life/robotics/evolvable hardware/generative and developmental systems/artificial immune systems), digital entertainment technologies and arts, evolutionary combinatorial optimization and metaheuristics, evolutionary machine learning, evolutionary multiobjective optimization, evolutionary numerical optimization, real world applications, search-based software engineering, theory and more.
Motivation
Real-world optimization problems often consist of several NP-hard combinatorial optimization problems that interact with each other. Such multi-component optimization problems are difficult to solve not only because of the contained hard optimization problems, but in particular, because of the interdependencies between the different components. Interdependence complicates a decision making by forcing each sub-problem to influence the quality and feasibility of solutions of the other sub-problems. This influence might be even stronger when one sub-problem changes the data used by another one through a solution construction process. Examples of multi-component problems are vehicle routing problems under loading constraints, maximizing material utilization while respecting a production schedule, and relocation of containers in a port while minimizing idle times of ships.
The goal of this competition is to provide a platform for researchers in computational intelligence working on multi-component optimization problems. The main focus of this competition is on the combination of TSP and Knapsack problems. However, we plan to extend this competition format to more complex combinations of problems (that have typically been dealt with individually in the past decades) in the upcoming years.
Website: https://www.egr.msu.edu/coinlab/blankjul/gecco19-thief/
You can find plenty of code, and instances there, as well as on the TTP project page, https://cs.adelaide.edu.au/~optlog/research/combinatorial.php
Submission: Deadline for this competition is June 30, 2019, Midnight, UTC-12
Evaluation: see our recent EMO’19 competition on this problem, i.e., https://www.egr.msu.edu/coinlab/blankjul/emo19-thief/
The winners will be announced at GECCO’19 in Prague, https://gecco-2019.sigevo.org/
Contact
Julian Blank (blankjul [at] egr.msu.edu)
Michigan State University
Computational Optimization and Innovation Laboratory (COIN)
East Lansing, MI 48824, USA
Markus Wagner (markus.wagner [at] adelaide.edu.au)
Optimisation and Logistics
The University of Adelaide, Australia
Adelaide, SA 5005, Australia
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