Evolving rule induction algorithms with multi-objective grammar-based genetic programming

2008 ◽  
Vol 19 (3) ◽  
pp. 283-309 ◽  
Author(s):  
Gisele L. Pappa ◽  
Alex A. Freitas
Keyword(s):  
Genetic Programming ◽  
Rule Induction ◽  
Multi Objective ◽  
Grammar Based Genetic Programming

scholarly journals Multiobjective grammar-based genetic programming applied to the study of asthma and allergy epidemiology

2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Rafael V. Veiga ◽  
Helio J. C. Barbosa ◽  
Heder S. Bernardino ◽  
João M. Freitas ◽  
Caroline A. Feitosa ◽  
...  
Keyword(s):  
Genetic Programming ◽  
Asthma And Allergy ◽  
Grammar Based Genetic Programming

scholarly journals Genetic Programming with Delayed Routing for Multi-Objective Dynamic Flexible Job Shop Scheduling

2020 ◽  
Author(s):  
Binzi Xu ◽  
Yi Mei ◽  
Yan Wang ◽  
Zhicheng Ji ◽  
Mengjie Zhang
Keyword(s):  
Genetic Programming ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Dynamic Environment ◽  
Accurate Information ◽  
Flexible Job Shop ◽  
Flexible Job Shop Scheduling ◽  
Shop Scheduling ◽  
Multi Objective ◽  
Conflicting Objectives

Dynamic Flexible Job Shop Scheduling (DFJSS) is an important and challenging problem, and can have multiple conflicting objectives. Genetic Programming Hyper-Heuristic (GPHH) is a promising approach to fast respond to the dynamic and unpredictable events in DFJSS. A GPHH algorithm evolves dispatching rules (DRs) that are used to make decisions during the scheduling process (i.e. the so-called heuristic template). In DFJSS, there are two kinds of scheduling decisions: the routing decision that allocates each operation to a machine to process it, and the sequencing decision that selects the next job to be processed by each idle machine. The traditional heuristic template makes both routing and sequencing decisions in a non-delay manner, which may have limitations in handling the dynamic environment. In this paper, we propose a novel heuristic template that delays the routing decisions rather than making them immediately. This way, all the decisions can be made under the latest and more accurate information. We propose three different delayed routing strategies, and automatically evolve the rules in the heuristic template by GPHH. We evaluate the newly proposed GPHH with Delayed Routing (GPHH-DR) on a multi-objective DFJSS that optimises the energy efficiency and mean tardiness. The experimental results show that GPHH-DR significantly outperformed the state-of-the-art GPHH methods. We further demonstrated the efficacy of the proposed heuristic template with delayed routing, which suggests the importance of delaying the routing decisions.

Exploring Multi-objective PSO and GRASP-PR for Rule Induction

2008 ◽  
pp. 73-84 ◽  
Author(s):  
Celso Y. Ishida ◽  
Andre B. de Carvalho ◽  
Aurora T. R. Pozo ◽  
Elizabeth F. G. Goldbarg ◽  
Marco C. Goldbarg
Keyword(s):  
Rule Induction ◽  
Multi Objective
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