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Memetic Computing

Memetic Computing OnlineFirst articles

05.10.2021 | Regular research paper

Parameter adaptation in multifactorial evolutionary algorithm for many-task optimization

The advent of multifactorial optimization (MFO) has made a wind of change in intelligence computation in general and specifically in evolutionary computing. Based on the implicit parallelism of population-based search, MFO optimizes different …

23.09.2021 | Regular research paper

System-in-package design using multi-task memetic learning and optimization

System-in-Package (SiP) is an advanced packaging technology and developing rapidly in semiconductor industry. Electronic modules of this package type are individual integrated systems for specific applications. Therefore, those modules are usually …

18.09.2021 | Regular research paper

Multi-lingual character handwriting framework based on an integrated deep learning based sequence-to-sequence attention model

Online signals are rich in dynamic features such as trajectory chronology, velocity, pressure and pen up/down movements. Their offline counterparts consist of a set of pixels. Thus, online handwriting recognition accuracy is generally better than …

21.08.2021 | Regular research paper Open Access

Modelling other agents through evolutionary behaviours

Modelling other agents is a challenging topic in artificial intelligence research particularly when a subject agent needs to optimise its own decisions by predicting their behaviours under uncertainty. Existing research often leads to a monotonic …

21.08.2021 | Regular research paper

Solving binary multi-objective knapsack problems with novel greedy strategy

This paper shows that the many greedy strategies that have been designed to repair infeasible solutions to multi-objective knapsack problems (MOKPs) with small item differences perform poorly when item differences are large. To effectively solve …

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Über diese Zeitschrift

Memetic Computing's goals are:

  • To be an outlet for high quality research in hybrid metaheuristics (including evolutionary hybrids) for optimization, control and design in continuous and discrete optimization domains. We seek to dissolve the barriers separating metaheuristics, exact and approximation algorithms research and to bring forth a renewed impetus towards the investigation and understanding of promising new hybrid algorithmic technologies.
  • To go beyond current search methodologies towards innovative research on the emergence of cultural artifacts such as game, trade and negotiation strategies and, more generally, rules of behavior as they apply to, for example, robotic, multi-agent and artificial life systems.
  • Ultimately, Memetic Computing aspires to serve as a focal publication where the latest results in Natural Computation, Artificial Intelligence, Machine Learning, Operational Research and Natural Sciences (e.g. cognitive, animal and insect's behavior, etc.) are fuzzed together in novel ways in order to transcend the intrinsic limitations of a single discipline.
  • Potential authors are invited to submit original research articles for publication consideration. Reviews and short communications may also be considered.

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