To address the problems of single evolutionary approach, decreasing diversity, inhomogeneity, and meaningfulness in destruction process when teaching–learning-based optimization (TLBO) algorithm solves no-wait flow-shop-scheduling problem, multi-strategy discrete (MSDTLBO) is introduced. Considering differences between individuals, redefined from student’s point view, giving basic integer seque...

Received Mar 17, 2017 Revised Aug 7, 2017 Accepted Sep 1, 2017 This paper discusses economic load dispatch Problem is modeled with nonconvex functions. These are problem are not solvable using a convex optimization techniques. So there is a need for using a heuristic method. Among such methods Teaching and Learning Based Optimization (TLBO) is a recently known algorithm and showed promising res...

This paper focuses on expanding and evaluating an automatic generation control (AGC) system of a hydrothermal system by modelling the appropriate generation rate constraints to operate practically in an economic manner. The hydro area is considered with an electric governor and the thermal area is modelled with a reheat turbine. Furthermore, the integral controllers and electri...

In this paper the performance of four well-known metaheuristics consisting of Artificial Bee Colony (ABC), Biogeographic Based Optimization (BBO), Harmony Search (HS) and Teaching Learning Based Optimization (TLBO) are investigated on optimal domain decomposition for parallel computing. A clique graph is used for transforming the connectivity of a finite element model (FEM) into that of the cor...

The energy consumption of a data center is the critical research issue, i.e. Virtual Machine (VM) placements to satisfy the resource requirements with minimum energy consumptions and active servers. The Multi-Objective Virtual Machine Placement (MOVMP) is a representation of a kind of combinatorial optimization problem. In this paper, Teaching Learning Based Optimization (TLBO) is used to solve...

This paper presents a new algorithm to optimize the reactive reserve. As the amount of reactive reserves at generating station is a measure of voltage stability. A new approach for scheduling of reactive power control variables for voltage stability enhancement using teaching-learning-based optimization (TLBO) has been developed. An objective function selected for maximization of reactive reser...