Mardé Helbig

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Mardé Helbig. Solving dynamic multi-objective optimisation problems using vector evaluated particle swarm opti-Abstract Most optimisation problems in everyday life are not static in nature, have multiple objectives and at least two of the objectives are in conflict with one another. However, most research focusses on either static multi-objective(More)
—The vector evaluated particle swarm optimisation (VEPSO) algorithm is a multi-swarm variation of particle swarm optimisation (PSO) used to solve static multi-objective optimi-sation problems (SMOOPs). Recently, VEPSO was extended to the dynamic VEPSO (DVEPSO) algorithm to solve dynamic multi-objective optimisation problems (DMOOPs) that have at least one(More)
Optimisation problems occur in many situations and aspects of modern life. In reality, many of these problems are dynamic in nature, where changes can occur in the environment that influence the solutions of the optimisation problem. Many methods use a weighted average approach to the multiple objectives. However, generally a dynamic multi-objective(More)
Algorithms that solve Dynamic Multi-Objective Optimisation Problems (DMOOPs) should be tested on benchmark functions to determine whether the algorithm can overcome specific difficulties that can occur in real-world problems. However, for Dynamic Multi-Objective Optimisation (DMOO), no standard benchmark functions are used. A number of DMOOPs have been(More)