Results 41 to 50 of about 149,503 (282)

On the path-avoidance vertex-coloring game

open access: yes, 2011
For any graph $F$ and any integer $r\geq 2$, the \emph{online vertex-Ramsey density of $F$ and $r$}, denoted $m^*(F,r)$, is a parameter defined via a deterministic two-player Ramsey-type game (Painter vs.\ Builder).
Mütze, Torsten, Spöhel, Reto
core   +3 more sources

Greedy Strategies with Multiobjective Optimization for Investment Portfolio Problem Modeling

open access: yesComputational Intelligence and Neuroscience, 2022
The ultimate purpose of portfolio investment is to reduce investment risk and improve total return on the premise of ensuring reasonable allocation of capital. In this paper, we build a quantitative model to advise on trading based on the price movement of Bitcoin and gold between 2016 and 2021; our goal is to maximize profit while minimizing risk.
Xinchen Zhang   +3 more
openaire   +2 more sources

A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem

open access: yesAlgorithms, 2017
The dynamic vehicle routing problem (DVRP) is a variant of the Vehicle Routing Problem (VRP) in which customers appear dynamically. The objective is to determine a set of routes that minimizes the total travel distance.
Shifeng Chen, Rong Chen, Jian Gao
doaj   +1 more source

The recoverability of network controllability with respect to node additions

open access: yesNew Journal of Physics, 2023
Network controllability is a critical attribute of dynamic networked systems. Investigating methods to restore network controllability after network degradation is crucial for enhancing system resilience.
Fenghua Wang, Robert E Kooij
doaj   +1 more source

Task Release Control for Decision Making Queues [PDF]

open access: yes, 2010
We consider the optimal duration allocation in a decision making queue. Decision making tasks arrive at a given rate to a human operator. The correctness of the decision made by human evolves as a sigmoidal function of the duration allocated to the task.
Bullo, Francesco   +3 more
core   +2 more sources

Calpain small subunit homodimerization is robust and calcium‐independent

open access: yesFEBS Letters, EarlyView.
Calpains dimerize via penta‐EF‐hand (PEF) domains. Using single‐molecule force spectroscopy, we measured the strength and kinetics of PEF–PEF homodimer binding. The interaction is robust, shows a transient conformational step before dissociation, and remains largely insensitive to Ca2+.
Nesha May O. Andoy   +4 more
wiley   +1 more source

A Novel Genetic Algorithm using Helper Objectives for the 0-1 Knapsack Problem [PDF]

open access: yes, 2014
The 0-1 knapsack problem is a well-known combinatorial optimisation problem. Approximation algorithms have been designed for solving it and they return provably good solutions within polynomial time.
Dong, Hongbin, He, Feidun, He, Jun
core  

Projection-Based and Look Ahead Strategies for Atom Selection

open access: yes, 2011
In this paper, we improve iterative greedy search algorithms in which atoms are selected serially over iterations, i.e., one-by-one over iterations. For serial atom selection, we devise two new schemes to select an atom from a set of potential atoms in ...
Chatterjee, Saikat   +3 more
core   +1 more source

Establishment of a humanized patient‐derived xenograft mouse model of high‐grade serous ovarian cancer for preclinical evaluation of combination immunotherapy

open access: yesMolecular Oncology, EarlyView.
We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric   +10 more
wiley   +1 more source

Distributed Submodular Maximization with Limited Information

open access: yes, 2017
We consider a class of distributed submodular maximization problems in which each agent must choose a single strategy from its strategy set. The global objective is to maximize a submodular function of the strategies chosen by each agent. When choosing a
Gharesifard, Bahman, Smith, Stephen L.
core   +1 more source

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