Results 51 to 60 of about 20,541 (191)
Particle algorithms for optimization on binary spaces
, 2011 We discuss a unified approach to stochastic optimization of pseudo-Boolean objective functions based on particle methods, including the cross-entropy method and simulated annealing as special cases.
Schäfer, Christian
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Non-linear great deluge with learning mechanism for solving the course timetabling problem [PDF]
, 2009 International ...
Landa-Silva, D. +3 more
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Nonparametric Comparison of Two Dynamic Parameter Setting Methods in a Meta-Heuristic Approach [PDF]
Journal of Systemics, Cybernetics and Informatics, 2007 Meta-heuristics are commonly used to solve combinatorial problems in practice. Many approaches provide very good quality solutions in a short amount of computational time; however most meta-heuristics use parameters to tune the performance of the meta ...
Seyhun HEPDOGAN +3 more
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Bio-Inspired Meta-Heuristics for Emergency Transportation Problems
Algorithms, 2014 Emergency transportation plays a vital role in the success of disaster rescue and relief operations, but its planning and scheduling often involve complex objectives and search spaces. In this paper, we conduct a survey of recent advances in bio-inspired
Min-Xia Zhang, Bei Zhang, Yu-Jun Zheng
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Nurse Scheduling with Opposition-Based Parallel Harmony Search Algorithm
Journal of Intelligent Systems, 2019 One of the advances made in the management of human resources for the effective implementation of service delivery is the creation of personnel schedules.
Cetin Yagmur Ece, Sarucan Ahmet
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Exploiting heterogeneity for cost efficient 5G base station deployment using meta‐heuristics
IET Networks, 2020 A key concern in the design of 5G is the radio access network, which is expected to be significantly denser and more advanced, with considerably higher infrastructure and power consumption cost than that of conventional mobile network standards.
David Aondoakaa +2 more
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Complex & Intelligent SystemsMulti-objective optimization (MOO) endeavors to identify optimal solutions from a finite array of possibilities. In recent years, deep reinforcement learning (RL) has exhibited promise through its well-crafted heuristics in tackling NP-hard combinatorial
Qi Wang, Chengwei Zhang, Bin Hu
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Hybrid Meta-Heuristics for Robust Scheduling [PDF]
The production and delivery of rapidly perishable goods in distributed supply networks involves a number of tightly coupled decision and optimization problems regarding the just-in-time production scheduling and the routing of the delivery vehicles in ...
Dekker, R. +3 more
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A multi-arm bandit neighbourhood search for routing and scheduling problems [PDF]
, 2016 Local search based meta-heuristics such as variable neighbourhood search have achieved remarkable success in solving complex combinatorial problems.
Chen, Yujie +3 more
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Energy loss optimization of run-off-road wheels applying imperialist competitive algorithm
Information Processing in Agriculture, 2014 The novel imperialist competitive algorithm (ICA) has presented outstanding fitness on various optimization problems. Application of meta-heuristics has been a dynamic studying interest of the reliability optimization to determine idleness and ...
Hamid Taghavifar, Aref Mardani
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