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Multi-Objective A* Algorithm for the Multimodal Multi-Objective Path Planning Optimization

2021 IEEE Congress on Evolutionary Computation (CEC), 2021
In this paper, we consider the multimodal multi-objective path planning (MMOPP) optimization, which is the main topic of a special session in IEEE CEC 2021. The MMOPP aims at finding all the Pareto optimal paths from a start area to a goal area on a grid map, while passing through several designated must-visit areas.
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Multi‐objective ensemble generation

WIREs Data Mining and Knowledge Discovery, 2015
Ensemble methods that combine a committee of machine‐learning models, each known as a member or base learner, have gained research interests in the past decade. One interest on ensemble generation involves the multi‐objective approach, which attempts to generate both accurate and diverse members that fulfill the theoretical requirements of good ...
Shenkai Gu, Ran Cheng, Yaochu Jin
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On the power of multi-objects

1997
In the standard ``single-object'''' model of shared-memory computing, it is assumed that a process accesses at most one shared object in each of its steps. In this paper, we consider a more powerful variant---the ``multi-object'''' model---in which each process may access *any* finite number of shared objects atomically in each of its steps. We present
Prasad Jayanti, Sanjay Khanna
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Multi-objective diversity maintenance

Proceedings of the 8th annual conference on Genetic and evolutionary computation, 2006
Paul Snijders Kunstmatige Intelligentie Groningen University Grote Kruisstraat 2/1 9712 TS Groningen, The Netherlands P.Snijders@ai.rug.nl Edwin D. de Jong Institute of Information and Computing Sciences Utrecht University PO Box 80.089 3508 TB Utrecht, The Netherlands dejong@cs.uu.nl Bart de Boer Kunstmatige Intelligentie Groningen University Grote ...
Snijders, P.   +3 more
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Hyper multi-objective evolutionary algorithm for multi-objective optimization problems

Soft Computing, 2016
Multi-objective optimization problems (MOPs) are very common in practice. To solve MOPs, many kinds of multi-objective evolutionary algorithms (MOEAs) are proposed. However, different MOEAs have different performances for different MOPs. Therefore, it is a time-consuming task to choose a suitable MOEA for a given problem.
Weian Guo   +3 more
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An improved multi-objective particle swarm optimizer for multi-objective problems

Expert Systems with Applications, 2010
This paper proposes an improved multi-objective particle swarm optimizer with proportional distribution and jump improved operation, named PDJI-MOPSO, for dealing with multi-objective problems. PDJI-MOPSO maintains diversity of new found non-dominated solutions via proportional distribution, and combines advantages of wide-ranged exploration and ...
Shang-Jeng Tsai   +5 more
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Automatic Configuration of Multi-objective Optimizers and Multi-objective Configuration

2019
Heuristic optimizers are an important tool in academia and industry, and their performance-optimizing configuration requires a significant amount of expertise. As the proper configuration of algorithms is a crucial aspect in the engineering of heuristic algorithms, a significant research effort has been dedicated over the last years towards moving this
Bezerra, Leonardo C.T.   +2 more
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Multi-objective Decisions

1989
A sign of maturity is the recognition that one can’t have everything. Compromise and trade-off are almost always unavoidable in real life decision situations, not only when several parties with non-coincident interests are involved but also when one own’s objectives or desires compete with one another for attention or priorities.
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Multi-objective branch and bound

European Journal of Operational Research, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Anthony Przybylski, Xavier Gandibleux
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Multi-Object Tracking in Video

Real-Time Imaging, 1999
This paper reports on tracking of multiple objects using color histogram backprojection and motion cues. Four tasks which facilitate this are discussed. The first is an adaptive color histogram backprojection (which builds upon the works of Swain and Ballard) and its application to tracking of multiple objects in video sequences.
Johnson I. Agbinya, David Rees
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