• Publications
  • Influence
A Competitive-Cooperative Coevolutionary Paradigm for Dynamic Multiobjective Optimization
  • C. Goh, K. Tan
  • Computer Science
  • IEEE Trans. Evol. Comput.
  • 1 February 2009
This paper proposes a new coevolutionary paradigm that hybridizes competitive and cooperative mechanisms observed in nature to solve multiobjective optimization problems and to track the Pareto front in a dynamic environment. Expand
Heuristic methods for vehicle routing problem with time windows
Each of the heuristics developed to Solomon's 56 VRPTW 100-customer instances are applied, and yielded 18 solutions better than or equivalent to the best solution ever published for these problems. Expand
Multiobjective Deep Belief Networks Ensemble for Remaining Useful Life Estimation in Prognostics
A multiobjective deep belief networks ensemble (MODBNE) method that employs a multiobjectives evolutionary algorithm integrated with the traditional DBN training technique to evolve multiple DBNs simultaneously subject to accuracy and diversity as two conflicting objectives is proposed. Expand
An Investigation on Noisy Environments in Evolutionary Multiobjective Optimization
  • C. Goh, K. Tan
  • Mathematics, Computer Science
  • IEEE Transactions on Evolutionary Computation
  • 1 June 2007
Three noise-handling features are proposed based upon the analysis of empirical results, including an experiential learning directed perturbation operator that adapts the magnitude and direction of variation according to past experiences for fast convergence and a possibilistic archiving model based on the concept of possibility and necessity measures to deal with problem of uncertainties. Expand
A Multi-Facet Survey on Memetic Computation
A comprehensive multi-facet survey of recent research in memetic computation is presented and includes simple hybrids, adaptive hybrids and memetic automaton. Expand
Precise-Spike-Driven Synaptic Plasticity: Learning Hetero-Association of Spatiotemporal Spike Patterns
Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. Expand
Evolutionary Multitasking for Multiobjective Continuous Optimization: Benchmark Problems, Performance Metrics and Baseline Results
Nine test problems for multi-task multi-Objective optimization (MTMOO), each of which consists of two multiobjective optimization tasks that need to be solved simultaneously, are suggested. Expand
Evolutionary algorithms with dynamic population size and local exploration for multiobjective optimization
A novel incrementing multiobjective evolutionary algorithm (IMOEA) with dynamic population size that is computed adaptively according to the online discovered tradeoff surface and its desired population distribution density and incorporates the method of fuzzy boundary local perturbation with interactive local fine tuning for broader neighborhood exploration. Expand
A Hybrid Multiobjective Evolutionary Algorithm for Solving Vehicle Routing Problem with Time Windows
A hybrid multiobjective evolutionary algorithm (HMOEA) that incorporates various heuristics for local exploitation in the evolutionary search and the concept of Pareto's optimality for solving multiobjectives optimization in VRPTW is proposed. Expand
A Multiobjective Memetic Algorithm Based on Particle Swarm Optimization
In this paper, a new memetic algorithm (MA) for multiobjective (MO) optimization is proposed, which combines the global search ability of particle swarm optimization with a synchronous local searchExpand