Evolutionary multi-level robust solution search for noisy multi-objective optimisation problems with different noise levels

Multi-objective Binary Search Optimisation

A location-allocation model in the multi-level supply chain with multi-objective evolutionary approach

In the current competitive conditions, all the manufacturers’ efforts are focused on increasing the customer satisfaction as well as reducing the production and delivery costs; thus, there is an increasing concentration on the structure and principles of supply chain (SC). Accordingly, the present research investigated simultaneous optimization of the total costs of a chain and customer satisfa...

Evolutionary Population Dynamics and Multi-Objective Optimisation Problems

Problems for which many objective functions are to be simultaneously optimised are widely encountered in science and industry. These multiobjective problems have also been the subject of intensive investigation and development recently for metaheuristic search algorithms such as ant colony optimisation, particle swarm optimisation and extremal optimisation. In this chapter, a unifying framework...

Evolutionary Multi-Objective Robust Optimization

A multi-tier adaptive grid algorithm for the evolutionary multi-objective optimisation of complex problems

The multi-tier Covariance Matrix Adaptation Pareto Archived Evolution Strategy (m-CMA-PAES) is an evolutionary multi-objective optimisation (EMO) algorithm for real-valued optimisation problems. It combines a nonelitist adaptive grid based selection scheme with the efficient strategy parameter adaptation of the elitist CovarianceMatrix Adaptation Evolution Strategy (CMA-ES). In the original CMA...