abstract this paper presents a multiobjective power control algorithm that updates the transmitted power based on local information. the proposed algorithm is expanded by using multiobjective optimization schemes. the objectives to be optimized in this paper are determined so as to reduce the sinr fluctuations as well as maintaining the sinr to an acceptable level with minimizing an average tra...

Vehicular Ad hoc NETworks (VANETs) are a major component recently used in the development of Intelligent Transportation Systems (ITSs). VANETs have a highly dynamic and portioned network topology due to the constant and rapid movement of vehicles. Currently, clustering algorithms are widely used as the control schemes to make VANET topology less dynamic for Medium Access Control (MAC), routing ...

In this reach work, a well performing approach in the context of multiobjective evolutionary algorithm (MOEA) is investigated due to its complexity. This approach called NSCCGA is based upon a previously introduced approach called NSGA-II. NSCCGA performs better than NSGA-II but with a heavy load of computational complexity. Here, a novel approach called GBCCGA is introduced based on MOCCGA wit...

In this article we build multi-objective hyperheuristics (MOHHs) using the multi-objective evolutionary algorithm NSGA-II for solving irregular 2D cutting stock problems under a bi-objective minimization schema, having a trade-off between the number of sheets used to fit a finite number of pieces and the time required to perform the placement of these pieces. We solve this problem using a multi...

One of the challenges which electrical power industry has been facing nowadays is adaptation system to energy transition taking place before our very eyes. With increasing share Renewable Energy Sources (RES) in production, development electromobility and environmental awareness society, must constantly evolve meet its expectations regarding a reliable electricity supply. This paper presents is...

The classification of survival in severe burnt patients is an on-going problem. In this paper we propose a multiobjective optimisation model with constraints to obtain fuzzy classification models based on the criteria of accuracy and interpretability. We also describe a multiobjective evolutionary approach for fuzzy classification based on data with real and discrete attributes. This approach i...

Today’s logistic systems in companies depend on optimum solutions of Facility Location-Allocation (FLA) problems in order to minimize cost values the company is dealing with. Therefore, FLA plays an important role in nowadays business environment. In this paper, a Hybrid Genetic Algorithm (HGA) is proposed to solve FLA. The HGA is a combination of Genetic Algorithm and Tabu Search while NSGA II...

A kind of unrelated parallel machines scheduling problem is discussed. The memberships of fuzzy due dates denote the grades of satisfaction with respect to completion times with jobs. Objectives of scheduling are to maximize the minimum grade of satisfaction while makespan is minimized in the meantime. Two kind of genetic algorithms are employed to search optimal solution set of the problem. Bo...

In the last two decades, multiobjective optimization has become main stream and various multiobjective evolutionary algorithms (MOEAs) have been suggested in the field of evolutionary computing (EC) for solving hard combinatorial and continuous multiobjective optimization problems. Most MOEAs employ single evolutionary operators such as crossover, mutation and selection for population evolution...