An Evolutionary Programming Hyper-heuristic with Co-evolution for CHeSC’11
نویسنده
چکیده
We present an Evolutionary Programming Hyper-heuristic (EPH) implemented for the Cross-Domain Heuristic Search Challenge 2011. The proposed method combines an evolutionary programming approach and co-evolution. The solving process of EPH consists in evolving a population of solutions by applying heuristics sequences. The heuristics sequences are also in a population and evolve according to their performances.
منابع مشابه
Hyper-Heuristic Based on Iterated Local Search Driven by Evolutionary Algorithm
This paper proposes an evolutionary-based iterative local search hyper-heuristic approach called Iterated Search Driven by Evolutionary Algorithm Hyper-Heuristic (ISEA). Two versions of this algorithm, ISEAchesc and ISEA-adaptive, that differ in the re-initialization scheme are presented. The performance of the two algorithms was experimentally evaluated on six hard optimization problems using ...
متن کاملCo-evolving add and delete heuristics
Hyper-heuristics are (meta-)heuristics that operate at a high level to choose or generate a set of low-level (meta-)heuristics to solve difficult search and optimisation problems. Evolutionary algorithms are well-known natureinspired meta-heuristics that simulate Darwinian evolution. In this article, we introduce an evolutionary-based hyper-heuristic in which a set of low-level heuristics compe...
متن کاملImproving Performance of a Hyper-heuristic Using a Multilayer Perceptron for Vehicle Routing
A hyper-heuristic is a heuristic optimisation method which generates or selects heuristics (move operators) based on a set of components while solving a computationally difficult problem. Apprenticeship learning arises while observing the behaviour of an expert in action. In this study, we use a multilayer perceptron (MLP) as an apprenticeship learning algorithm to improve upon the performance ...
متن کاملEvolutionary Hyper - Heuristics for Heuristic Selection
Hyper-heuristics are an emerging that has received increasing attention in the last years. As they are black box optimization techniques that work on higher level of abstraction, they have many real world application. This work aims to explore the possibilities of application of evolutionary algorithms and related methods in the field of hyper-heuristics. Their properties make them a particular...
متن کاملSelf-Adaptive Differential Evolution Hyper-Heuristic with Applications in Process Design
The paper presents a differential evolution (DE)-based hyper-heuristic algorithm suitable for the optimization of mixed-integer non-linear programming (MINLP) problems. The hyper-heuristic framework includes self-adaptive parameters, an ε-constrained method for handling constraints, and 18 DE variants as low-level heuristics. Using the proposed approach, we solved a set of classical test proble...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2011