Complexity and variety of modern multiobjective optimisation problems result in the
emergence of numerous search techniques, from traditional mathematical programming to …

Placement of optimally sized distributed generator (DG) units at optimal locations in the
radial distribution networks can play a major role in improving the system performance. The …

Modern software development builds on external Web services reuse as a promising way
that allows developers delivering feature-rich software by composing existing Web service …

Hypervolume (HV) and inverted generational distance (IGD) have been frequently used as
performance indicators to evaluate the quality of solution sets obtained by evolutionary …

In data center companies, cloud computing can host multiple types of heterogeneous virtual
machines (VMs) and provide many features, including flexibility, security, support, and even …

Decomposition is a representative method for handling many-objective optimization
problems with evolutionary algorithms. Classical decomposition scheme relies on a set of …

The discrete probabilistic bicriteria optimization problem (DPBOP) is a discrete optimization
problem with probabilistic criteria which should be optimized simultaneously. The DPBOP …

Multi-Objective Evolutionary Algorithms (MOEAs) have been applied successfully for solving
real-world multi-objective problems. Their success can depend highly on the configuration of …

The major difficulty in multi-objective optimization evolutionary algorithms (MOEAs) is how to
find an appropriate solution which is able to converge towards the true Pareto Front with …

Efficient design and management of water distribution networks is critical for conservation of
water resources and minimization of both energy requirements and maintenance costs …