ADEMO'16
Advances in Decomposition-based
Evolutionary Multiobjective Optimization
1st ADEMO Special session @ IEEE-WCCI/CEC 2016
25-29 July, Vancouver, Canada
The purpose of this special session is to promote the design, study, and validation of generic approaches for solving multiobjective optimization problems based on the concept of decomposition. Decompositionbased Evolutionary Multiobjective Optimization (DEMO) encompasses any technique, concept or framework that takes inspiration from the “divide and conquer” paradigm, by essentially breaking a multiobjective optimization problem into several subproblems for which solutions for the original global problem are computed and aggregated in a cooperative manner. This simple idea, which is rather standard in computer science and information systems, allows to open up new exciting research perspectives and challenges both at the fundamental level of our understanding of multiobjective problems, and in terms of designing and implementing new efficient algorithms for solving them. Generally speaking, the special session will focus on stochastic evolutionary approaches for which decomposition is performed with respect to the objective space, typically by means of scalarizing functions like in the MOEA/D framework. We, however, encourage contributions reporting advances with respect to other decomposition techniques operating in the decision space; or other hybrid approaches taking inspiration from operations research and mathematical programming. In fact, many different DMOEAs variants have been proposed, studied and applied to various application domains in recent years. However, DEMOs are still in their very early infancy, since only few basic design principles have been established compared to the huge body of literature dedicated to other wellestablished approaches (e.g. Pareto ranking, indicatorbased techniques, etc), and relatively few research forums have been dedicated to the study of DEMO approaches and their unification. The main goal of the proposed session is to encourage research studies that systematically investigate the critical issues in DMOEAs at the aim of understanding their key ingredients and their main dynamics, as well a to develop solid and generic principles for designing them. The long term goal is to contribute to the emergence of a general and unified methodology for the design, the tuning and the performance assessment of DEMOs.
The special session will be a nice opportunity for researchers in the evolutionary and multiobjective optimization filed to exchange their recent ideas and advances on the design and analysis of DEMO approaches. In this respect, we are welcoming high quality papers in theoretical, developmental, implementational, and applied aspects of DEMO approaches. More particularly, the special session will encourage original research contributions that address new and existing DEMOs, their contributions and relationships to other methodologies dedicated to multiobjective optimization in terms of: algorithmic components, decomposition strategies, collaboration among different search procedures, design of new specialized search procedures, parallel and distributed implementations, incorporation of user interaction, combination and hybridization with other traditional (heuristic or exact) techniques, strategies for dealing with many objectives, noisy problems, and expensive problems, problem solving and applications, etc. The main focus will be on eliciting the main design principles that lead to effective and efficient cooperative search procedures among the so defined single or multiple objective subproblems.
The topics of interests include (but are not limited to) the following issues :
Analysis of algorithmic components and performance assessment of DEMO approaches
Experimental and theoretical investigations on the accuracy of the underlying decomposition strategies, e.g. scalarizing functions techniques, multiple reference points, variable grouping, etc.
Adaptive, selfadaptive, and tuning aspects for the parameter setting and configuration of DEMO approaches
Design and analysis of new DEMO approaches dedicated to specific combinatorial, constrained and/or continuous domains
Effective hybridization of singleobjective solvers with DEMO approaches, i.e., plugand play algorithms based on traditional single objective evolutionary algorithms and meta heuristics, such as: Genetic Algorithms (GAs), Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Covariance Matrix Evolution Strategy (CMAES), Scatter Search (SS), etc
Adaptation and analysis of DEMO approaches in the context of large scale and many objective problem solving
Application of DEMO for realworld problem solving
Design and implementation of DEMO approaches in massively parallel and large scale distributed environment (e.g., GPUs, Clusters, Grids, etc)
Software tools for the design implementation and performance assessment of DEMO approaches
Paper submission deadline is on January 15, 2016.
Submission procedure, deadlines and paper format are same than the IEEE-WCCI/CEC'16 main conference. In particular, we recall that papers must be submitted through the IEEE WCCI 2016 online submission system, while selecting the ADEMO special session under the list of research topics in the submission system.
Saúl Zapotecas Martínez (saul.zapotecas@gmail.com)
SHINSHU University, Japan
DOLPHIN, Inria Lille Nord Europe, France
Bilel Derbel (bilel.derbel@univlille1.fr)
University Lille 1, CRIStAL CNRS UMR9189, France
DOLPHIN, Inria Lille Nord Europe, France
Qingfu Zhang (qingfu.zhang@cityu.edu.hk)
City University of Hong Kong, Hong Kong
Carlos A. Coello Coello (ccoello@cs.cinvestav.mx)
CINVESTAVIPN, Mexico