In the field of multiobjective optimization, important efforts have been made in recent years to generate global Pareto fronts uniformly distributed. A new multiobjective evolutionary algorithm, called ↗−MOGA, has been designed to converge towards ΘP , a reduced but well distributed representation of the Pareto set ΘP . The algorithm achieves good convergence and distribution of the Pareto fron...

Genetic programming (GP) is extensively used for structure and parameter tuning of control systems. This paper describes an application of genetic programming for Pareto biobjective design of polynomial based controllers for some common time-delay systems. In this way, a multi-objective uniform-diversity genetic programming proposed and used for polynomial controller evolution. The ε-eliminatio...

Design of any complex system entails many objectives to reach and constraints to satisfy. This multi–objective nature of the problem ensures that the technology solution is always a compromise between conflicting objectives. The purpose of this paper is to demonstrate the application of Niched Pareto genetic algorithm as a relatively fast and straightforward method for obtaining technology sets...

Pareto optimality is capable of striking the optimal trade-off amongst the diverse conflicting QoS requirements of routing in wireless multihop networks. However, this comes at the cost of increased complexity owing to searching through the extended multi-objective search-space. We will demonstrate that the powerful quantum-assisted dynamic programming optimization framework is capable of circu...

This paper proposes a novel approach to generate a uniform distribution of the optimal solutions along the Pareto frontier. We make use of a standard mathematical technique for optimization namely line search and adapt it so that it will be able to generate a set of solutions uniform distributed along the Pareto front. To validate the method, numerical bi-criteria examples are considered. The m...

Multicriteria optimization applications can be implemented using Pareto optimization techniques including evolutionary Multicriteria optimization algorithms. Many real world applications involve multiple objective functions and the Pareto front may contain a very large number of points. Choosing a solution from such a large set is potentially intractable for a decision maker. Previous approache...

In this paper we present a new image thresholding method based on a multiobjective Genetic Algorithm using the Pareto optimality approach. We aim to optimize multiple criteria in order to increase the segmentation quality. Thus, we’ve adapted the well known Non Domination Sorting Genetic Algorithm for this purpose so that it takes into consideration the contribution of the objective functions i...

The aim of this work was to compare different approaches to VMAT optimization (biological vs. physical DVH-based) in two commercial treatment planning systems (TPS) for head and neck and prostate cases, using Pareto fronts. VMAT vs. IMRT Pareto front comparison was additionally performed in order to benchmark the optimizer efficiency and VMAT plan quality for each TPS. Three prostate and three ...

In this paper, we first propose four-layer optimization for UMTS coverage area: (i) cell-oriented intra-SGSN layer, which is optimized RA areas covering the intra-SGSN signaling cost, paging cost and RA load balancing, (ii) RA-oriented intra-MSC layer, which is optimized location areas covering the intra-MSC signaling cost and LA load balancing,(iii) RA-oriented inter-SGSN layer, which is optim...

Transactions with quantitative values are commonly seen in real-world applications. Fuzzy mining algorithms have thus been developed recently to induce linguistic knowledge from quantitative databases. In fuzzy data mining, the membership functions have a critical influence on the final mining results. How to effectively decide the membership functions in fuzzy data mining thus becomes very imp...