In this study, we proposed a discrete teaching-learning-based optimisation (DTLBO) for solving the flowshop rescheduling problem. Five types of disruption events, namely machine breakdown, new job arrival, cancellation of jobs, job processing variation and job release variation, are considered simultaneously. The proposed algorithm aims to minimise two objectives, i.e., the maximal completion t...

The determination of photovoltaic (PV) parameters is great importance for the reliability solar system operation, continuity load power consumption, and control management energy source. Therefore, this study proposes an advanced backtracking search optimization algorithm (BSA) equipped with teaching learning-based (TLBO), named TLBOBSA, to accurately simulate PV model. During evaluation propos...

Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having ‘g’ operations is performed on ‘g’ operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem...

This study proposes an algorithm to allocate different types of flexible AC transmission system (FACTS) in power systems. The main objective this is maximize profit by minimizing the system’s operating cost including FACTS devices (FDs) installation cost. Dynamic and steady state restrictions with loads uncertainty are included problem formulation. overall solved using both teaching learning ba...

Machining is the essential activity of a manufacturing organization and milling is one of them. The economy growth rate of a country depends upon the innovation and research in manufacturing sectors. In this paper an attempt has been made to identify the gap in optimization of process parameters in milling operations through extensive literature review. Literature review revealed that researche...

Generally, a major power system problem is dynamic economic dispatch problem (DEDP) for multiple fuel power plants. This problem is a nonlinear and nonsmooth optimization problem when multi fuel effects and valve-point effects are considered. In this contribution, Improved Radial Basis Function Network (IRBFN) and Weighted Probabilistic Neural Network (WPNN) are compared and employed to forecas...

This study presents a hybrid metaheuristic algorithm to obtain optimum designs for steel space buildings. The optimum design problem of three-dimensional steel frames is mathematically formulated according to provisions of LRFD-AISC (Load and Resistance factor design of American Institute of Steel Construction). Design constraints such as the strength requirements of structural members, the dis...

Accurate travel route optimization is essential to promote and grow tourism in modern society. This paper investigates a problem alongside the urban railway line proposes hybrid teaching–learning-based (HTLBO) algorithm. First, mathematical programming model established minimize total traveling time, which routes between different cities have be appropriately determined. Then, metaheuristic nam...