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GECCO
2000
Springer
170views Optimization» more  GECCO 2000»
13 years 11 months ago
A Comparison of Genetic Algorithms for the Dynamic Job Shop Scheduling Problem
The majority of the research using evolutionary algorithms for the Job Shop Scheduling Problem (JSSP) has studied only the static JSSP. Few evolutionary algorithms have been appli...
Manuel Vázquez, L. Darrell Whitley
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
13 years 11 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace
EVOW
2004
Springer
14 years 1 months ago
Constructing Dynamic Optimization Test Problems Using the Multi-objective Optimization Concept
Abstract. Dynamic optimization using evolutionary algorithms is receiving increasing interests. However, typical test functions for comparing the performance of various dynamic opt...
Yaochu Jin, Bernhard Sendhoff
EVOW
2008
Springer
13 years 9 months ago
A Memory Enhanced Evolutionary Algorithm for Dynamic Scheduling Problems
Abstract. This paper describes a memory enhanced evolutionary algorithm (EA) approach to the dynamic job shop scheduling problem. Memory enhanced EAs have been widely investigated ...
Gregory J. Barlow, Stephen F. Smith
GECCO
2007
Springer
137views Optimization» more  GECCO 2007»
14 years 2 months ago
Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case
The focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, t...
Peter A. N. Bosman, Han La Poutré