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Tuning Meta-Heuristics Using Multi-agent Learning in a Scheduling System [chapter]

Ivo Pereira, Ana Madureira, P. B. de Moura Oliveira, Ajith Abraham
2013 Lecture Notes in Computer Science  
Based on Multi-Agent Learning concepts, this article propose a Case-based Reasoning module in order to solve the parametertuning problem in a Multi-Agent Scheduling System.  ...  In complexity theory, scheduling problem is considered as a NPcomplete combinatorial optimization problem.  ...  Acknowledgments This work is supported by FEDER Funds through the "Programa Operacional Factores de Competitividade -COMPETE" program and by National  ... 
doi:10.1007/978-3-642-45318-2_8 fatcat:y344gz65tzewbokq4mmfzzi2dy

Multi-agent based hyper-heuristics for multi-objective flexible job shop scheduling: A case study in an aero-engine blade manufacturing plant

Yong Zhou, Jian-Jun Yang, Lian-Yu Zheng
2019 IEEE Access  
INDEX TERMS Scheduling, flexible job shop, multi-agent, hyper-heuristics, genetic programming. NOMENCLATURE NSGAII Nondominated sorting genetic algorithm II.  ...  In the paper, a case study focusing on multi-objective flexible job shop scheduling problem (MO-FJSP) in an aero-engine blade manufacturing plant is presented.  ...  ACKNOWLEDGEMENT The authors would like to thank Qing-miao Liao and Peng-cheng Fang for their support and contributions during the development of this work.  ... 
doi:10.1109/access.2019.2897603 fatcat:zpysik5q6ranrbele6r7zz2pqa

Improved Genetic Algorithm Approach based on New Virtual Crossover Operators for Dynamic Job Shop Scheduling

Kaouther Ben Ali, Achraf Jabeur Telmoudi, Said Gattoufi
2020 IEEE Access  
Other studies have presented different inspired hyper-heuristics approaches such as the work of Park et al. [29] that have proposed a new genetic programming based hyper-heuristic.  ...  REFERENCES Different scheduling problems are classified based on their complexity in different production lines: flow shop, job shop, and open shop, etc.  ... 
doi:10.1109/access.2020.3040345 fatcat:ufeh74vxcjfgriqk46e5ugc6cy

Solving multi-objective job shop problem using nature-based algorithms: new Pareto approximation features

Jarosław Rudy, Dominik Żelazny
2015 An International Journal of Optimization and Control: Theories & Applications  
Multi-objective job shop problems (MOJSP) were rarely studied.  ...  We implement and compare two multi-agent nature-based methods, namely ant colony optimization (ACO) and genetic algorithm (GA) for MOJSP.  ...  Hyper-volume indicator measures the area covered by the approximated Pareto fronts for each of algorithms. In order to bound this area, a reference point is used.  ... 
doi:10.11121/ijocta.01.2015.00232 fatcat:jk7ug6idlbdizgvpovnmpemgim

Modeling and solution methods for hybrid flow shop scheduling problem with job rejection

Mohamadreza Dabiri, Mehdi Yazdani, Bahman Naderi, Hassan Haleh
2021 Operational Research  
Additionally, this paper studies the efficacy of job rejection noting the scheduling for a real-world hybrid flow shop in the tile industry production system.  ...  Also, this paper exhibits two innovative heuristic algorithms, which are presented to discover fast solutions for the problem along with five meta-heuristics are adapted to solve large-sized problems in  ...  Dabiri et al. (2019) used a genetic algorithm, 3 heuristic algorithms and an approximation algorithm to solve a scheduling problem involving rejection in a multi-machine set in a flow-shop scheduling  ... 
doi:10.1007/s12351-021-00629-2 fatcat:33sxe5n7znhtxls3fnttt7dg5a

Comparisons of bi-objective genetic algorithms for hybrid flowshop scheduling with sequence-dependent setup times

S.M. Mousavi, M. Zandieh, M. Amiri
2012 International Journal of Production Research  
A B S T R A C T Multi-criteria sequence dependent setup times scheduling problems exist almost everywhere in real modern manufacturing world environments.  ...  Among them, Sequence Dependent Setup Times-Multi-Objective Hybrid Flowshop Scheduling Problem (SDST-MOHFSP) has been an intensifying attention of researchers and practitioners in the last three decades  ...  Another hybrid in this category are hyper-heuristics.  ... 
doi:10.1080/00207543.2010.543178 fatcat:ch5qv36nyjedvojvytrmjh6wpu

Learning iterative dispatching rules for job shop scheduling with genetic programming

Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan
2013 The International Journal of Advanced Manufacturing Technology  
The overall goal of this thesis is to develop a genetic programming based hyper-heuristic (GPHH) approach for automatic heuristic design of reusable and competitive dispatching rules in job shop scheduling  ...  A coevolution genetic programming method to evolve scheduling policies for dynamic multiobjective job shop scheduling problems".  ...  multi-objective genetic programming based hyper-heuristic (MO-GPHH) method to evolve dispatching rules for DJSS.2.  ... 
doi:10.1007/s00170-013-4756-9 fatcat:rgnsvur5nrh3lhpzc2j5s7agta

Swarm Intelligence in Multiple and Many Objectives Optimization: A Survey and Topical Study on EEG Signal Analysis [chapter]

B. S. P. Mishra, Satchidanand Dehuri, Sung-Bae Cho
2015 Studies in Computational Intelligence  
This paper systematically presents the Swarm Intelligence (SI) methods for optimization of multiple and many objective problems.  ...  A pragmatic topical study on the behavior of real ants, bird flocks, and honey bees in solving EEG signal analysis completes the survey followed by discussion and extensive number of relevant references  ...  [136] proposed an MOABC for handling Multi-objective job shop scheduling problem. Wang et al.  ... 
doi:10.1007/978-3-662-46309-3_2 fatcat:j3cgruamfzbfljgqu5gdpahloa

A Comparison between Two Modified NSGA-II Algorithms for Solving the Multi-objective Flexible Job Shop Scheduling Problem

Aydin Teymourifar, Gurkan Ozturk, Ozan Bahadir
2018 Universal Journal of Applied Mathematics  
In this paper, two modified NSGA-II algorithms have been suggested for solving the multi-objective flexible job shop scheduling problem.  ...  Many evolutionary algorithms have been used to solve multi-objective scheduling problems. NSGA-II is one of them that is based on the Pareto optimality concept and generally obtains good results.  ...  This reference-point-based many-objective algorithm emphasizes population members that are non-dominated, yet close to a set of supplied reference points.  ... 
doi:10.13189/ujam.2018.060302 fatcat:f2vepnbj4fd6bmrcu4xtvw4jk4

A quarter century of particle swarm optimization

Shi Cheng, Hui Lu, Xiujuan Lei, Yuhui Shi
2018 Complex & Intelligent Systems  
Particle swarm optimization (PSO) is a population-based stochastic algorithm modeled on the social behaviors observed in flocking birds.  ...  Through the convergent operation and divergent operation, individuals in PSO group and diverge in the search space/objective space.  ...  Flexible job shop scheduling problem (FJSP) For FJSP, Nouiri investigated a two stage particle swarm optimization (2S-PSO), which consists of PSO after initial swarm for objective of makespan and PSO after  ... 
doi:10.1007/s40747-018-0071-2 fatcat:rajjkozus5govjy7kgnwix5edm

Table of Contents

2020 2020 IEEE Symposium Series on Computational Intelligence (SSCI)  
Cruz-Duarte and Hugo Terashima-Marin .......... 3133 A Genetic Programming Hyper-Heuristic Approach to Design High-Level Heuristics for Dynamic Workflow Scheduling in Cloud Kirita-Rose Escott Escott, Hui  ...  ESCO2: Multi-Objective Scheduling/Production Scheduling, Chair: Yi Mei A Tailored NSGA-III for Multi-objective Flexible Job Shop Scheduling Yali Wang, Bas van Stein, Thomas Baeck and Michael Emmerich  ... 
doi:10.1109/ssci47803.2020.9308155 fatcat:hyargfnk4vevpnooatlovxm4li

A review on implementation of meta-heuristic approaches for layout problems in dynamic business environment

Parveen Sharma, Sandeep Singhal
2016 International Journal of Multivariate Data Analysis  
Tabu search (TS), genetic algorithm (GA), particle swarm optimisation (PSO), and ant colony optimisation (ACO) are several typically used methods by researchers for layout optimisation.  ...  The purpose of this research paper is to present a review on the implementation of meta-heuristics approaches for handling the problem of facility layout in a dynamic environment.  ...  Wang and Tang (2011) presented an improved adaptive GA based on hormone modulation mechanism for job-shop scheduling problem of industries.  ... 
doi:10.1504/ijmda.2016.081076 fatcat:7hy2t5us6rex3lbmobcnhqkxta

Parallel-machine scheduling to minimize tardiness penalty and power cost

Kuei-Tang Fang, Bertrand M.T. Lin
2013 Computers & industrial engineering  
Traditional research on machine scheduling focuses on job allocation and sequencing to optimize certain objective functions that are defined in terms of job completion times.  ...  A computational study is conducted to investigate the performances of the proposed heuristics and the PSO algorithm.  ...  The authors are also grateful to the reviewers for their valuable comments.  ... 
doi:10.1016/j.cie.2012.10.002 fatcat:4wkmonq3jbf5xnb4dxoonyehsm

A hyper-heuristic approach to automated generation of mutation operators for evolutionary programming

Libin Hong, John H. Drake, John R. Woodward, Ender Özcan
2018 Applied Soft Computing  
In this paper, we use genetic programming to automatically generate mutation operators for an evolutionary programming system, testing the proposed approach over a set of function classes, which represent  ...  The proposed method is able to outperform existing human designed mutation operators with statistical significance in most cases, with competitive results observed for the rest.  ...  GP has also been used to automatically design schedule policies for dynamic multi-objective job shop scheduling [24] , to evolve ensembles of dispatching rules for the job shop scheduling problem [25  ... 
doi:10.1016/j.asoc.2017.10.002 fatcat:qvhkjbr3pbepvd6tpkbc722iyi

A Survey on Integration of Optimization and Project Management Tools for Sustainable Construction Scheduling

Borna Dasović, Mario Galić, Uroš Klanšek
2020 Sustainability  
Focusing on construction scheduling, an in-depth achievements survey on the integration of heuristics methods, mathematical programming and special solving methods with conventional PMT as well as optimization-based  ...  Following a brief introduction, the optimization platform for construction scheduling is given in the article.  ...  This publication is a part of research project "Monitoring of Tower Cranes' Key Reliability Parameters for Safety and Performance-MonitorCRANE" funded by the Faculty of Civil Engineering and Architecture  ... 
doi:10.3390/su12083405 fatcat:ylec37cwobe2jl5wvijd2py46u
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