Due to the drastic rise in multimedia content, digital images have become a major carrier of data. Generally, are communicated or archived via wireless communication changes, and significance data security gets increased. In order accomplish security, encryption is an effective technique which used encrypt using secret keys such way that it not readable by hacker. this view, study focuses on de...

Resource allocation is a non-polynomial complete problem in the cloud data center that selects proper resources to execute many fine computational granularity tasks. Customer requirements and capacity of applications change frequently. To bridge gap between frequently changing customer requirement available infrastructure for services, we propose dynamic resource strategy using an adaptive mult...

In this paper, teaching–learning-based optimization (TLBO) is proposed to solve flexible job shop scheduling problem (FJSP) based on the integrated approach with an objective to minimize makespan. An FJSP is an extension of basic job-shop scheduling problem. There are two sub problems in FJSP. They are routing problem and sequencing problem. If both the sub problems are solved simultaneously, t...

In this study, to enhance the optimization process, especially in the structural engineering field two well-known algorithms are merged together in order to achieve an improved hybrid algorithm. These two algorithms are Teaching-Learning Based Optimization (TLBO) and Harmony Search (HS) which have been used by most researchers in varied fields of science. The hybridized algorithm is called A Di...

Meta-heuristics optimization methods are important techniques for optimal design of the engineering systems. Numerous methods, inspired by different nature phenomena, have been introduced in the literature. A new modified version of Teaching-Learning-Based Optimization (TLBO) Algorithm is introduced in this paper. TLBO, as a parameter free algorithm, is based on the learning procedure of studen...

A key component of the design and operation power transmission systems is optimal flow (OPF) problem. To solve this problem, several optimization algorithms have been developed. The primary objectives program are to minimize fuel costs, reduce emissions, improve voltage profiles, losses. OPF considered one most challenging problems due its nonconvexity significant computational difficulty. Teac...

This study provides a teaching-learning-based optimization (TLBO) path planning method for an autonomous vehicle in cluttered environment, which takes into account smoothness and the possibility of collision with nearby obstacles. The problem is tackled as multiobjective order to plan efficient that allows travel autonomously crowded settings. TLBO algorithm is used find ideal path, goals fin...

This paper is engrossed in the usage of metaheuristic optimization methods named JAYA algorithm and teacher learning based (TLBO) algorithm, which deal with objective function optimal power flow (OPF) problem. TLBO Jaya are parameter-free algorithms, reduce complexity algorithms. The this to real losses maintain voltages tap positions within their limits. IEEE-39 bus system data considered for ...

Reliable prediction of individual learning performance can facilitate timely support to students and improve the experience. In this study, two well-known machine-learning techniques, that is, vector machine (SVM) artificial neural network (ANN), are hybridized by teaching–learning-based optimizer (TLBO) reliably predict student exam (fail-pass classes final scores). For defined classification ...