A Proposal to Hybridize Multi-Objective Evolutionary Algorithms with Non-gradient Mathematical Programming Techniques

نویسندگان

  • Saúl Zapotecas Martínez
  • Carlos A. Coello Coello
چکیده

The hybridization of multi-objective evolutionary algorithms (MOEAs) with mathematical programming techniques has gained increasing popularity in the specialized literature in the last few years. However, such hybrids normally rely on the use of gradients and, therefore, normally consume a high number of extra objective function evaluations in order to estimate the gradient information required. The use of direct (nonlinear) optimization techniques has been, however, less common in the specialized literature, although several hybrids of this sort have been proposed for single-objective evolutionary algorithms. This paper proposes a hybridization between a well-known MOEA (the NSGAII) and two direct search methods (Nelder and Mead’s method and the golden section algorithm). The aim of the proposed approach is to combine the global search mechanisms of the evolutionary algorithm with the local search mechanisms provided by the aforementioned mathematical programming techniques, such that a more efficient (i.e., with a lower number of objective function evaluations) approach can be produced.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Use of Gradient-Free Mathematical Programming Techniques to Improve the Performance of Multi-Objective Evolutionary Algorithms

In spite of the current widespread use of Multi-Objective Evolutionary Algorithms (MOEAs) for solving Multi-objective Optimization Problems (MOPs), their computational cost (measured in terms of fitness function evaluations performed) remains as one of their main limitations when applied to real-world applications. In order to address this issue, a variety of hybrid approaches combining mathema...

متن کامل

Using composite ranking to select the most appropriate Multi-Criteria Decision Making (MCDM) method in the optimal operation of the Dam reservoir

In this study, the performance of the algorithms of whale, Differential evolutionary, crow search, and Gray Wolf optimization were evaluated to operate the Golestan Dam reservoir with the objective function of meeting downstream water needs. Also, after defining the objective function and its constraints, the convergence degree of the algorithms was compared with each other and with the absolut...

متن کامل

Solving ‎‎‎Multi-objective Optimal Control Problems of chemical ‎processes ‎using ‎Hybrid ‎Evolutionary ‎Algorithm

Evolutionary algorithms have been recognized to be suitable for extracting approximate solutions of multi-objective problems because of their capability to evolve a set of non-dominated solutions distributed along the Pareto frontier‎. ‎This paper applies an evolutionary optimization scheme‎, ‎inspired by Multi-objective Invasive Weed Optimization (MOIWO) and Non-dominated Sorting (NS) strategi...

متن کامل

MULTI-OBJECTIVE ROUTING AND SCHEDULING IN FLEXIBLE MANUFACTURING SYSTEMS UNDER UNCERTAINTY

The efficiency of transportation system management plays an important role in the planning and operation efficiency of flexible manufacturing systems. Automated Guided Vehicles (AGV) are part of diversified and advanced techniques in the field of material transportation which have many applications today and act as an intermediary between operating and storage equipment and are routed and contr...

متن کامل

A new multi-objective mathematical model for a Citrus supply chain network design: Metaheuristic algorithms

Nowadays, the citrus supply chain has been motivated by both industrial practitioners and researchers due to several real-world applications. This study considers a four-echelon citrus supply chain, consisting of gardeners, distribution centers, citrus storage, and fruit market. A Mixed Integer Non-Linear Programming (MINLP) model is formulated, which seeks to minimize the total cost and maximi...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008