Abstract Development of efficient multi-objective evolutionary algorithms (MOEAs) has
provided effective tools to solve environmental/economic dispatch (EED) problems. EED is a …

Power generation system largely depends on fossil fuels to generate electricity. Due to
various reasons, the reserves of fossil fuels are declining and will become too expensive in …

When solving constrained optimization problems (COPs) by evolutionary algorithms, the
search algorithm plays a crucial role. In general, we expect that the search algorithm has the …

Abstract Incremental Artificial Bee Colony algorithm with Local Search (IABC-LS) is one of
efficient variant of artificial bee colony optimization which was successfully applied to …

This paper presents the application of backtracking search algorithm (BSA) for solving an
economic/emission dispatch (EED) problem as a multi-objective optimization problem. BSA …

Economic dispatch is carried out at the energy control center to find out the optimal output of
thermal generating units such that power balance criterion is met, unit operating limits are …

This paper presents a-multiobjective-teaching-learning-based optimization algorithm to
solve the dynamic economic emission dispatch problem. Teaching-learning-based …

Replicating and comparing computational experiments in applied evolutionary computing
may sound like a trivial task. Unfortunately, it is not so. Namely, many papers do not …

The paper proposes a multi-objective biogeography based optimization (MO-BBO) algorithm
to design optimal placement of phasor measurement units (PMU) which makes the power …

Abstract Economic Load Dispatch (ELD) is an imperative assignment in contemporary
aggressive power demand market. Dearth of power generation in all dimensions of energy …