Skip to Main Content

Advertisement

MIT Press Direct, home
header search
Search
Advanced Search
Skip Nav Destination

On Using Surrogates with Genetic Programming

Evolutionary Computation (2015) 23 (3): 343–367.
This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.
Surrogate-assisted cooperative learning genetic programming for the resource-constrained project scheduling problem with stochastic activity durations and transfer times
  • Haohua Zhang
  • Erik Demeulemeester
  • Lubo Li
  • Sijun Bai
Computers & Operations Research (2025) 173: 106816.
Multiobjective Dynamic Flexible Job Shop Scheduling With Biased Objectives via Multitask Genetic Programming
  • Fangfang Zhang
  • Gaofeng Shi
  • Yi Mei
  • Mengjie Zhang
IEEE Transactions on Artificial Intelligence (2025) 6 (1): 169.
Survey on Genetic Programming and Machine Learning Techniques for Heuristic Design in Job Shop Scheduling
  • Fangfang Zhang
  • Yi Mei
  • Su Nguyen
  • Mengjie Zhang
IEEE Transactions on Evolutionary Computation (2024) 28 (1): 147.
Efficient ontology matching through compact linear genetic programming with surrogate-assisted local search
  • Xingsi Xue
  • Jerry Chun-Wei Lin
  • Tong Su
Swarm and Evolutionary Computation (2024) 91: 101758.
A Global and Local Surrogate-Assisted Genetic Programming Approach to Image Classification
  • Qinglan Fan
  • Ying Bi
  • Bing Xue
  • Mengjie Zhang
IEEE Transactions on Evolutionary Computation (2024) 28 (3): 718.
Knowledge-transfer based genetic programming algorithm for multi-objective dynamic agile earth observation satellite scheduling problem
  • Luona Wei
  • Ming Chen
  • Lining Xing
  • Qian Wan
  • Yanjie Song
  • Yuning Chen
  • Yingwu Chen
Swarm and Evolutionary Computation (2024) 85: 101460.
Co-evolution genetic programming-based hyper-heuristics for the stochastic project scheduling problem with resource transfer and idle costs
  • Haohua Zhang
  • Lubo Li
  • Sijun Bai
  • Jingwen Zhang
Swarm and Evolutionary Computation (2024) 90: 101678.
Genetic Programming With Lexicase Selection for Large-Scale Dynamic Flexible Job Shop Scheduling
  • Meng Xu
  • Yi Mei
  • Fangfang Zhang
  • Mengjie Zhang
IEEE Transactions on Evolutionary Computation (2024) 28 (5): 1235.
Enhancing generalization in genetic programming hyper-heuristics through mini-batch sampling strategies for dynamic workflow scheduling
  • Yifan Yang
  • Gang Chen
  • Hui Ma
  • Sven Hartmann
  • Mengjie Zhang
Information Sciences (2024) 678: 120975.
Evolve ensemble rules automatically for the block spatial scheduling under dynamic environments via surrogate-assisted cooperative evolution genetic programming
  • Lubo Li
  • Haohua Zhang
  • Sijun Bai
International Journal of Production Research 1.
A surrogate-assisted dual-tree genetic programming framework for dynamic resource constrained multi-project scheduling problem
  • HaoJie Chen
  • XinYu Li
  • Liang Gao
International Journal of Production Research (2024) 62 (16): 5631.
An improved genetic programming hyper-heuristic for the dynamic flexible job shop scheduling problem with reconfigurable manufacturing cells
  • Haoxin Guo
  • Jianhua Liu
  • Yue Wang
  • Cunbo Zhuang
Journal of Manufacturing Systems (2024) 74: 252.
A multi-surrogate genetic programming hyper-heuristic algorithm for the manufacturing project scheduling problem with setup times under dynamic and interference environments
  • Lubo Li
  • Haohua Zhang
  • Sijun Bai
Expert Systems with Applications (2024) 250: 123854.
Learning Heuristics With Different Representations for Stochastic Routing
  • Ya-Hui Jia
  • Yi Mei
  • Mengjie Zhang
IEEE Transactions on Cybernetics (2023) 53 (5): 3205.
Task Relatedness-Based Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling
  • Fangfang Zhang
  • Yi Mei
  • Su Nguyen
  • Kay Chen Tan
  • Mengjie Zhang
IEEE Transactions on Evolutionary Computation (2023) 27 (6): 1705.
Leveraging explainable AI for enhanced decision making in humanitarian logistics: An Adversarial CoevoluTION (ACTION) framework
  • Su Nguyen
  • Greg O’Keefe
  • Sobhan Arisian
  • Kerry Trentelman
  • Damminda Alahakoon
International Journal of Disaster Risk Reduction (2023) 97: 104004.
Dispatching Rules Selection Mechanism Using Support Vector Machine for Genetic Programming in Job Shop Scheduling
  • Shady Salama
  • Toshiya Kaihara
  • Nobutada Fujii
  • Daisuke Kokuryo
IFAC-PapersOnLine (2023) 56 (2): 7814.
Feature selection approach for evolving reactive scheduling policies for dynamic job shop scheduling problem using gene expression programming
  • Salama Shady
  • Toshiya Kaihara
  • Nobutada Fujii
  • Daisuke Kokuryo
International Journal of Production Research (2023) 61 (15): 5029.
Instance Selection-Based Surrogate-Assisted Genetic Programming for Feature Learning in Image Classification
  • Ying Bi
  • Bing Xue
  • Mengjie Zhang
IEEE Transactions on Cybernetics (2023) 53 (2): 1118.
Machine learning enhancing metaheuristics: a systematic review
  • Artur Leandro da Costa Oliveira
  • André Britto
  • Renê Gusmão
Soft Computing (2023) 27 (21): 15971.
Multitask Multiobjective Genetic Programming for Automated Scheduling Heuristic Learning in Dynamic Flexible Job-Shop Scheduling
  • Fangfang Zhang
  • Yi Mei
  • Su Nguyen
  • Mengjie Zhang
IEEE Transactions on Cybernetics (2023) 53 (7): 4473.
Knowledge Transfer Genetic Programming With Auxiliary Population for Solving Uncertain Capacitated Arc Routing Problem
  • Mazhar Ansari Ardeh
  • Yi Mei
  • Mengjie Zhang
  • Xin Yao
IEEE Transactions on Evolutionary Computation (2023) 27 (2): 311.
Learning dispatching rules via novel genetic programming with feature selection in energy-aware dynamic job-shop scheduling
  • Adilanmu Sitahong
  • Yiping Yuan
  • Ming Li
  • Junyan Ma
  • Zhiyong Ba
  • Yongxin Lu
Scientific Reports (2023) 13 (1)
A pairwise ranking estimation model for surrogate-assisted evolutionary algorithms
  • Tomohiro Harada
Complex & Intelligent Systems (2023) 9 (6): 6875.
Automated design of priority rules for resource-constrained project scheduling problem using surrogate-assisted genetic programming
  • Jingyu Luo
  • Mario Vanhoucke
  • José Coelho
Swarm and Evolutionary Computation (2023) 81: 101339.
Surrogate model for memetic genetic programming with application to the one machine scheduling problem with time-varying capacity
  • Francisco J. Gil-Gala
  • María R. Sierra
  • Carlos Mencía
  • Ramiro Varela
Expert Systems with Applications (2023) 233: 120916.
Instance-Rotation-Based Surrogate in Genetic Programming With Brood Recombination for Dynamic Job-Shop Scheduling
  • Fangfang Zhang
  • Yi Mei
  • Su Nguyen
  • Kay Chen Tan
  • Mengjie Zhang
IEEE Transactions on Evolutionary Computation (2023) 27 (5): 1192.
Collaborative Multifidelity-Based Surrogate Models for Genetic Programming in Dynamic Flexible Job Shop Scheduling
  • Fangfang Zhang
  • Yi Mei
  • Su Nguyen
  • Mengjie Zhang
IEEE Transactions on Cybernetics (2022) 52 (8): 8142.
Automated Coordination Strategy Design Using Genetic Programming for Dynamic Multipoint Dynamic Aggregation
  • Guanqiang Gao
  • Yi Mei
  • Bin Xin
  • Ya-Hui Jia
  • Will N. Browne
IEEE Transactions on Cybernetics (2022) 52 (12): 13521.
Genetic Programming With Niching for Uncertain Capacitated Arc Routing Problem
  • Shaolin Wang
  • Yi Mei
  • Mengjie Zhang
  • Xin Yao
IEEE Transactions on Evolutionary Computation (2022) 26 (1): 73.
Automated Design of Multipass Heuristics for Resource-Constrained Job Scheduling With Self-Competitive Genetic Programming
  • Su Nguyen
  • Dhananjay Thiruvady
  • Mengjie Zhang
  • Damminda Alahakoon
IEEE Transactions on Cybernetics (2022) 52 (9): 8603.
A similarity measure for Straight Line Programs and its application to control diversity in Genetic Programming
  • R. Rueda
  • M.P. Cuéllar
  • L.G.B. Ruiz
  • M.C. Pegalajar
Expert Systems with Applications (2022) 194: 116415.
A filtering genetic programming framework for stochastic resource constrained multi-project scheduling problem under new project insertions
  • HaoJie Chen
  • Guofu Ding
  • Jian Zhang
  • Rong Li
  • Lei Jiang
  • Shengfeng Qin
Expert Systems with Applications (2022) 198: 116911.
Genetic Programming With Knowledge Transfer and Guided Search for Uncertain Capacitated Arc Routing Problem
  • Mazhar Ansari Ardeh
  • Yi Mei
  • Mengjie Zhang
IEEE Transactions on Evolutionary Computation (2022) 26 (4): 765.
A novel feature selection for evolving compact dispatching rules using genetic programming for dynamic job shop scheduling
  • Salama Shady
  • Toshiya Kaihara
  • Nobutada Fujii
  • Daisuke Kokuryo
International Journal of Production Research (2022) 60 (13): 4025.
Automatic design for shop scheduling strategies based on hyper-heuristics: A systematic review
  • Haoxin Guo
  • Jianhua Liu
  • Cunbo Zhuang
Advanced Engineering Informatics (2022) 54: 101756.
Effective and interpretable dispatching rules for dynamic job shops via guided empirical learning
  • Cristiane Ferreira
  • Gonçalo Figueira
  • Pedro Amorim
Omega (2022) 111: 102643.
An efficient genetic programming approach to design priority rules for resource-constrained project scheduling problem
  • Jingyu Luo
  • Mario Vanhoucke
  • José Coelho
  • Weikang Guo
Expert Systems with Applications (2022) 198: 116753.
Correlation-Guided Updating Strategy for Feature Selection in Classification With Surrogate-Assisted Particle Swarm Optimization
  • Ke Chen
  • Bing Xue
  • Mengjie Zhang
  • Fengyu Zhou
IEEE Transactions on Evolutionary Computation (2022) 26 (5): 1015.
Multitask Genetic Programming-Based Generative Hyperheuristics: A Case Study in Dynamic Scheduling
  • Fangfang Zhang
  • Yi Mei
  • Su Nguyen
  • Kay Chen Tan
  • Mengjie Zhang
IEEE Transactions on Cybernetics (2022) 52 (10): 10515.
Surrogate-assisted automatic evolving of dispatching rules for multi-objective dynamic job shop scheduling using genetic programming
  • Yannik Zeiträg
  • José Rui Figueira
  • Nuno Horta
  • Rui Neves
Expert Systems with Applications (2022) 209: 118194.
People-Centric Evolutionary System for Dynamic Production Scheduling
  • Su Nguyen
  • Mengjie Zhang
  • Damminda Alahakoon
  • Kay Chen Tan
IEEE Transactions on Cybernetics (2021) 51 (3): 1403.
Surrogate models in evolutionary single-objective optimization: A new taxonomy and experimental study
  • Hao Tong
  • Changwu Huang
  • Leandro L. Minku
  • Xin Yao
Information Sciences (2021) 562: 414.
Genetic programming-based hyper-heuristic approach for solving dynamic job shop scheduling problem with extended technical precedence constraints
  • Huali Fan
  • Hegen Xiong
  • Mark Goh
Computers & Operations Research (2021) 134: 105401.
Correlation Coefficient-Based Recombinative Guidance for Genetic Programming Hyperheuristics in Dynamic Flexible Job Shop Scheduling
  • Fangfang Zhang
  • Yi Mei
  • Su Nguyen
  • Mengjie Zhang
IEEE Transactions on Evolutionary Computation (2021) 25 (3): 552.
Reactive scheduling approach for solving a realistic flexible job shop scheduling problem
  • B. Mihoubi
  • B. Bouzouia
  • M. Gaham
International Journal of Production Research (2021) 59 (19): 5790.
Surrogate-Assisted Evolutionary Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling
  • Fangfang Zhang
  • Yi Mei
  • Su Nguyen
  • Mengjie Zhang
  • Kay Chen Tan
IEEE Transactions on Evolutionary Computation (2021) 25 (4): 651.
A Genetic Programming Approach for Evolving Variable Selectors in Constraint Programming
  • Su Nguyen
  • Dhananjay Thiruvady
  • Mengjie Zhang
  • Kay Chen Tan
IEEE Transactions on Evolutionary Computation (2021) 25 (3): 492.
Preserving Population Diversity Based on Transformed Semantics in Genetic Programming for Symbolic Regression
  • Qi Chen
  • Bing Xue
  • Mengjie Zhang
IEEE Transactions on Evolutionary Computation (2021) 25 (3): 433.
A learning-based two-stage optimization method for customer order scheduling
  • Zhongshun Shi
  • Hang Ma
  • Meiheng Ren
  • Tao Wu
  • Andrew J. Yu
Computers & Operations Research (2021) 136: 105488.

Advertisement

  • Online ISSN 1530-9304
  • Print ISSN 1063-6560
A product of The MIT Press
Newsletter sign up

MIT Press Direct

Information

MIT Press

Contact Us

© 2024 The MIT Press
Close Modal
This Feature Is Available To Subscribers Only

or Create an Account

Close Modal
Close Modal
This site uses cookies. By continuing to use our website, you are agreeing to our privacy policy. No content on this site may be used to train artificial intelligence systems without permission in writing from the MIT Press.
Accept