Genetic algorithms (GAs) are biologically inspired computing techniques, which tend to
mimic the basic Darwinian concepts of natural selection. They are highly robust and efficient …

Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

This paper considers the problem of sequence-dependent setup time hybrid flowshop
scheduling with the objectives of minimizing the makespan and sum of the earliness and …

This paper proposes a new two-stage optimization method for multi-objective supply chain
network design (MO-SCND) problem with uncertain transportation costs and uncertain …

Radiation shielding with light weight is of significance for nuclear facilities, especially for
mobile nuclear reactors. The design of radiation shielding is a complex multi-objective …

Industrial symbiosis is a promising approach for energy conservation and emission
reduction in the global industrial sector. The objective of this research is to optimize …

Due to efficacy and optimization potential of genetic and evolutionary algorithms, they are
used in learning and modeling especially with the advent of big data related problems. This …

We propose replacing the division operator used in genetic programming with an analytic
quotient (AQ) operator. We demonstrate that this AQ operator systematically yields lower …

An important issue in multi-objective optimisation is how to ensure that the obtained non-
dominated set covers the Pareto front as widely as possible. A number of techniques (eg …

A multi-objective and multi-level optimization procedure is developed for obtaining optimal
structural design of filament wound composite pipes in oil and gas industries. At the first …