Now showing items 41-50 of 102
Pre-scheduled colony size variation in dynamic environments
The performance of the MAX -MIN ant system (MMAS) in dynamic optimization problems (DOPs) is sensitive to the colony size. In particular, a large colony size may waste computational resources whereas a small colony size ...
Multiobjective optimization of the production process for ground granulated blast furnace slags
The production process of ground granulated blast furnace slag (GGBS) aims to produce products of the best grade and the highest yields. However, grade and yields are two competing objectives which can not be optimized at ...
An evolutionary dynamic multi-objective optimization algorithm based on center-point prediction and sub-population autonomous guidance
Dynamic multi-objective optimization problems (DMOPs) provide a challenge in that objectives conflict each other and change over time. In this paper, a hybrid approach based on prediction and autonomous guidance is proposed, ...
Benchmark Generator for the IEEE WCCI-2012 Competition on Evolutionary Computation for Dynamic Optimization Problems
(Brunel University, U.K., 2011-10)
Based on our previous benchmark generator for the IEEE CEC’09 Competition on Dynamic Optimization, this report updates the two benchmark instances where a new change type has been developed as well as a constraint to the ...
An Adaptive Local Search Algorithm for Real-Valued Dynamic Optimization
(IEEE Press, 2015-05)
This paper proposes a novel adaptive local search algorithm for tackling real-valued (or continuous) dynamic optimization problems. The proposed algorithm is a simple single-solution based metaheuristic that perturbs the ...
Pheromone modification strategy for the dynamic travelling salesman problem with weight changes
Ant colony optimization (ACO) algorithms have proved to be able to adapt in problems that change dynamically. One of the key issues for ACO when a change occurs is that the pheromone trails generated in the previous ...
A decomposition-based multiobjective evolutionary algorithm with angle-based adaptive penalty
A multiobjective evolutionary algorithm based on decomposition (MOEA/D) decomposes a multiobjective optimization problem (MOP) into a number of scalar optimization subproblems and optimizes them in a collaborative manner. ...
Towards Knowledge Driven Decision Support for Personalized Home-based Self-management of Chronic Diseases
(IEEE Press, 2015-08)
The use of ICT technologies to facilitate self-management for patients with chronic diseases attracts increasing attention in smart healthcare. Existing research has mainly focused on sensing and data processing technologies ...
Guest editorial: Memetic computing in the presence of uncertainties