parallel problem solving from nature 2023

18 th International Conference on

Parallel problem solving from nature ppsn 2024.

September 14 - 18, 2024 Hagenberg, Austria

Welcome to PPSN 2024!

The International Conference on Parallel Problem Solving From Nature is a biannual open forum fostering the study of natural models, iterative optimization heuristics search heuristics, machine learning, and other artificial intelligence approaches. We invite researchers and practitioners to present their work, ranging from rigorously derived mathematical results to carefully crafted empirical studies.

All information regarding the conference organization, call for papers/tutorials/workshops, submission, registration, venue, etc. will be provided and constantly updated on this website and on our social media channels. In case of any additional inquiries, please do not hesitate to contact us .

See you soon in beautiful Hagenberg, Austria!

Michael Affenzeller & Stephan Winkler PPSN 2024 Conference Chairs

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Registration is now open

April 16, 2024 Jan Zenisek --> Updates

The registration system “ConfTool” is now set up for PPSN 2024 and open to receive your registrations! The link to the registration system is https://www.conftool.net/ppsn2024 .

PPSN 2024 will take place from September 14-18, 2024 . Other important dates are: (deadline interpretation = end of the day, anywhere on earth)

• [Closed] Paper submission due: April 5, 2024 Extension: April 18, 2024
• [Closed] Tutorials/Workshop proposal submission due: February 9, 2024
• [Closed] Tutorials/Workshop acceptance notification: February 23, 2024
• Paper review due: May 20, 2024
• Paper acceptance notification: May 31, 2024
• Tutorials/Workshops: September 14–15, 2024
• Poster Sessions: September 16–18, 2024

PPSN 2024 will take place on the Campus of the University of Applied Sciences Upper Austria , located in the Softwarepark Hagenberg, Austria .

For more details regarding dates have a look at the pages for Calls and Program .

For more details regarding venue, travel, accomodation and tourism go to: Venue .

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Fh-prof. pd di dr. michael affenzeller, fh-prof. pd di dr. stephan winkler, mag. michaela beneder.

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17th PPSN 2022: Dortmund, Germany

16th PPSN 2020: Leiden, The Netherlands

15th PPSN 2018: Coimbra, Portugal

14th PPSN 2016: Edinburgh, UK

13th PPSN 2014: Ljubljana, Slovenia

12th PPSN 2012: Taormina, Italy

11th ppsn 2010: kraków, poland.

10th PPSN 2008: Dortmund, Germany

9th ppsn 2006: reykjavik, iceland.

8th PPSN 2004: Birmingham, UK

7th ppsn 2002: granada, spain, 6th ppsn 2000: paris, france, 5th ppsn 1998: amsterdam, the netherlands, 4th ppsn 1996: berlin, germany, 3rd ppsn 1994: jerusalem, israel, 2nd ppsn 1992: brussels, belgium, 1st ppsn 1990: dortmund, germany.

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Problem solving articles from across Nature Portfolio

Problem solving is the mental process of analyzing a situation, learning what options are available, and then choosing the alternative that will result in the desired outcome or some other selected goal.

Latest Research and Reviews

Forming cognitive maps for abstract spaces: the roles of the human hippocampus and orbitofrontal cortex

An fMRI study on a navigation task in multidimensional abstract spaces showed that the human hippocampus, entorhinal cortex, and orbitofrontal cortex collaborate in learning abstract space structures.

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States of epistemic curiosity interfere with memory for incidental scholastic facts

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Association of executive function with suicidality based on resting-state functional connectivity in young adults with subthreshold depression

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Spatially embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings

A fundamental question in neuroscience is what are the constraints that shape the structural and functional organization of the brain. By bringing biological cost constraints into the optimization process of artificial neural networks, Achterberg, Akarca and colleagues uncover the joint principle underlying a large set of neuroscientific findings.

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Reverse effect of home-use binaural beats brain stimulation

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Teaching of 21st century skills needs to be informed by psychological research

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Simulated brain solves problems

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Parallel problem solving from nature-- PPSN III : International Conference on Evolutionary Computation, the Third Conference on Parallel Problem Solving from Nature, Jerusalem, Israel, October 9-14, 1994 : proceedings

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Intelligent Cooperation by Solving a Two-Stage Production Assembly Scheduling Problem with a Heuristic Algorithm in Canned Food Plant

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• First Online: 03 May 2024
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• Meng Qiu 15 , 15 &
• Tsui-Ping Chung 15  

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

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• The International Conference on Smart Manufacturing, Industrial & Logistics Engineering (SMILE)

We consider a two-stage production assembly scheduling problem which includes processing stage and assembly stage. In first stage, the parts of these products are produced by these parallel machines, and each machine can process only one of these parts at a time. There is only one single assembly machine or a group of assembly workers in the second stage. In this problem, the objective is to minimize total completion time. The two-stage assembly scheduling problem is an NP-hard problem, so that it is very difficult and time consuming to obtain the optimal solution. This paper proposes a heuristic algorithm to solve the total completion time of two-stage assembly scheduling problem. Then, this algorithm is tested on the issue in different sizes and compare with the discrete particle swarm optimization (DPSO) algorithm. The results show that the proposed heuristic algorithm is a very efficient algorithm for assembly scheduling problem.

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Potts CN, Sevast’janov SV, Strusevich VA, Van Wassenhove LN, Zwaneveld CM (1995) The two-stage assembly scheduling problem: complexity and approximation. Oper Res 43:346–355

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School Business, Northeast Normal University, Changchun, China

Meng Qiu, Meng Qiu & Tsui-Ping Chung

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Runliang Dou

Sichuan University, Chengdu, China

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Qiu, M., Chung, TP. (2024). Intelligent Cooperation by Solving a Two-Stage Production Assembly Scheduling Problem with a Heuristic Algorithm in Canned Food Plant. In: Chien, CF., Dou, R., Luo, L. (eds) Proceedings of Industrial Engineering and Management. SMILE 2023. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-97-0194-0_13

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