A semi-definite programming (SDP) formulation of the multi-objective economic-emission dispatch problem is presented. The fuel cost and emission functions are represented by high order polynomial functions and this was shown to be a more accurate representation of the economic-emission dispatch...

The economic dispatch (ED) is one of the important optimization problems in power system generation for fuel cost saving. This paper proposes a hybrid variant of mean-variance mapping optimization (MVMO-SH) for solving such problem considering the non-convex objective functions. The new proposed...

Quantum-behaved particle swarm optimization (QPSO) is an efficient and powerful population-based optimization technique, which is inspired by the conventional particle swarm optimization (PSO) and quantum mechanics theories. In this paper, an improved QPSO named SQPSO is proposed, which combines...

This paper presents teaching–learning-based optimization algorithm for solving MAED (multi-area economic dispatch) problem with tie line constraints considering transmission losses, multiple fuels, valve-point loading and prohibited operating zones. TLBO (teaching–learning-based...

Open shop scheduling problems (OSSP) are highly significant in engineering and industry, involving critical scheduling challenges. The job type determines the duration required for material transfer between machines and remains unaffected by distance, eliminating any waiting time for transfers....

This paper proposes a new method called the enhanced charged system search algorithm in order to solve the reserve constrained dynamic optimal power flow. The optimal power flow (OPF) is applied to develop the corrective strategies and to make the least cost dispatches. The static OPF solutions...