Blockchain Privacy Through Merge Avoidance and Mixing Services

2021 ◽  
Vol 48 (4) ◽  
pp. 8-11
Author(s):  
Jefferson E. Simoes ◽  
Eduardo Ferreira ◽  
Daniel S. Menasch´e ◽  
Carlos A. V. Campos
Keyword(s):  
Optimization Problem ◽  
The Body ◽  
Np Hard ◽  
Fundamental Limits ◽  
Incentive Compatible ◽  
Impossibility Results ◽  
Privacy Level

Cryptocurrencies typically aim at preserving the privacy of their users. Different cryptocurrencies preserve privacy at various levels, some of them requiring users to rely on strategies to raise the privacy level to their needs. Among those strategies, we focus on two of them: merge avoidance and mixing services. Such strategies may be adopted on top of virtually any blockchain-based cryptocurrency. In this paper, we show that whereas optimal merge avoidance leads to an NP-hard optimization problem, incentive-compatible mixing services are subject to a certain class of impossibility results. Together, our results contribute to the body of work on fundamental limits of privacy mechanisms in blockchainbased cryptocurrencies.

The Minimum Stretch Spanning Tree Problem for Hamming Graphs and Higher-Dimensional Grids

2020 ◽  
Vol 20 (01) ◽  
pp. 2050004
Author(s):  
LAN LIN ◽  
YIXUN LIN
Keyword(s):  
Communication Networks ◽  
Spanning Tree ◽  
Optimization Problem ◽  
Maximum Distance ◽  
Np Hard ◽  
Graph Invariant ◽  
Minimum Value ◽  
Higher Dimensional ◽  
Hamming Graphs

The minimum stretch spanning tree problem for a graph G is to find a spanning tree T of G such that the maximum distance in T between two adjacent vertices is minimized. The minimum value of this optimization problem gives rise to a graph invariant σ(G), called the tree-stretch of G. The problem has been proved NP-hard. In this paper we present a general approach to determine the exact values σ(G) for a series of typical graphs arising from communication networks, such as Hamming graphs and higher-dimensional grids (including hypercubes).

COMPLEXITY OF SCENARIO-BASED PORTFOLIO OPTIMIZATION PROBLEM WITH VaR OBJECTIVE

2002 ◽  
Vol 13 (05) ◽  
pp. 671-679 ◽  
Author(s):  
XIAOGUANG YANG ◽  
SHUO TAO ◽  
RONGJUN LIU ◽  
MAOCHENG CAI
Keyword(s):  
Portfolio Optimization ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Np Hard ◽  
Portfolio Optimization Problem

In this paper we discuss the VaR-related portfolio optimization problems. We give a scenario-based formulation of the portfolio optimization problem with VaR objective and show that the problem is NP-hard.

Time-optimal trajectory planning method for six-legged robots under actuator constraints

2019 ◽  
Vol 233 (14) ◽  
pp. 4990-5002
Author(s):  
Zhijun Chen ◽  
Feng Gao
Keyword(s):  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Optimization Problem ◽  
The Body ◽  
Planning Method ◽  
Legged Robots ◽  
Legged Robot ◽  
Time Optimal ◽  
Actuator Constraints ◽  
Optimal Trajectory Planning

Current studies on time-optimal trajectory planning centers on cases with fixed base and only one end-effector. However, the free-floating body and the multiple legs of the legged robot make the current methods inapplicable. This paper proposes a time-optimal trajectory planning method for six-legged robots. The model of the optimization problem for six-legged robots is built by considering the base and the end-effectors separately. Both the actuator constraints and the gait cycle constraints are taken into account. A novel two-step optimization method is proposed to solve the optimization problem. The first step solves the time-optimal trajectory of the body and the second step solves the time-optimal trajectory of the swinging legs. Finally, the method is applied to a six-parallel-legged robot and validated by experiments on the prototype. The results show that the velocity of the optimized gait is improved by 17.8% in contrast to the non-optimized one.

Solution to the 0-1 Multidimensional Knapsack Problem Based on DNA Computation

2011 ◽  
Vol 58-60 ◽  
pp. 1767-1772
Author(s):  
Kee Rong Wu ◽  
Chung Wei Yeh
Keyword(s):  
Knapsack Problem ◽  
Optimization Problem ◽  
Deoxyribonucleic Acid ◽  
Np Hard ◽  
Multidimensional Knapsack Problem ◽  
Dna Computation ◽  
Multidimensional Knapsack ◽  
Operational Problem ◽  
Hard Problems ◽  
Computation Scheme

We proposed a two-layer scheme of Deoxyribonucleic acid (DNA) based computation, DNA-01MKP, to solve the typical NP-hard combinatorial optimization problem, 0-1 multidimensional knapsack problem (0-1 MKP). DNA-01MKP consists of two layers of procedures: (1) translation of the problem equations to strands and (2) solution of problems. For layer 1, we designed flexible well-formatted strands to represent the problem equations; for layer 2, we constructed the DNA algorithms to solve the 0-1 MKP. Our results revealed that this molecular computation scheme is able to solve the complicated operational problem with a reasonable time complexity of O(n×k), though it needs further experimental verification in the future. By adjusting the DNA-based procedures, the scheme may be used to resolve different NP-hard problems.

scholarly journals Are Stable Instances Easy?

2012 ◽  
Vol 21 (5) ◽  
pp. 643-660 ◽  
Author(s):  
YONATAN BILU ◽  
NATHAN LINIAL
Keyword(s):  
Polynomial Time ◽  
Discrete Optimization ◽  
Optimization Problem ◽  
Discrete Optimization Problem ◽  
Hard Problem ◽  
Np Hard ◽  
Max Cut Problem ◽  
Np Hard Problem ◽  
Hard Problems ◽  
Np Hard Problems

We introduce the notion of a stable instance for a discrete optimization problem, and argue that in many practical situations only sufficiently stable instances are of interest. The question then arises whether stable instances of NP-hard problems are easier to solve, and in particular, whether there exist algorithms that solve in polynomial time all sufficiently stable instances of some NP-hard problem. The paper focuses on the Max-Cut problem, for which we show that this is indeed the case.

Human Motion Capture with Sparse Inertial Sensors and Video

2020 ◽  
Author(s):  
Timo von Marcard
Keyword(s):  
Global Optimization ◽  
Optimization Problem ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Hybrid Approach ◽  
Human Motion ◽  
The Body ◽  
Sensor Data ◽  
Discrete Optimization Problem ◽  
Global Optimization Problem

This thesis explores approaches to capture human motions with a small number of sensors. In the first part of this thesis an approach is presented that reconstructs the body pose from only six inertial sensors. Instead of relying on pre-recorded motion databases, a global optimization problem is solved to maximize the consistency of measurements and model over an entire recording sequence. The second part of this thesis deals with a hybrid approach to fuse visual information from a single hand-held camera with inertial sensor data. First, a discrete optimization problem is solved to automatically associate people detections in the video with inertial sensor data. Then, a global optimization problem is formulated to combine visual and inertial information. The propose  approach enables capturing of multiple interacting people and works even if many more people are visible in the camera image. In addition, systematic inertial sensor errors can be compensated, leading to a substantial in...

An Novel Estimation of Distribution Algorithm for TSP

2013 ◽  
Vol 373-375 ◽  
pp. 1089-1092
Author(s):  
Fa Hong Yu ◽  
Wei Zhi Liao ◽  
Mei Jia Chen
Keyword(s):  
Optimization Problem ◽  
Population Diversity ◽  
Combinatorial Optimization Problem ◽  
Estimation Of Distribution Algorithm ◽  
Traveling Salesman ◽  
Estimation Of Distribution Algorithms ◽  
Np Hard ◽  
Estimation Of Distribution ◽  
Np Hard Problem ◽  
Distribution Algorithms

Estimation of distribution algorithms (EDAs) is a method for solving NP-hard problem. But it is hard to find global optimization quickly for some problems, especially for traveling salesman problem (TSP) that is a classical NP-hard combinatorial optimization problem. To solve TSP effectively, a novel estimation of distribution algorithm (NEDA ) is provided, which can solve the conflict between population diversity and algorithm convergence. The experimental results show that the performance of NEDA is effective.

Research on the Equipment Maintenance Tasks Scheduling Optimization Problem Based on GA

2012 ◽  
Vol 452-453 ◽  
pp. 750-754
Author(s):  
Yi Ma ◽  
Yu Lu ◽  
Li Yun Chen ◽  
Ping Gu
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Optimization Problem ◽  
New Method ◽  
Equipment Maintenance ◽  
Np Hard ◽  
Scheduling Optimization ◽  
Tasks Scheduling ◽  
Problem Design ◽  
The Military

Scientific maintenance tasks scheduling can improve maintenance effectiveness greatly. Aiming for the shortage of the research on the equipment maintenance tasks scheduling optimization (EMTSO) problem, this paper proposes a new method based on GA. The detail is as follows: Make the optimization model of the EMTSO problem by analyzing the characteristics of maintenance tasks scheduling systemically. Aiming for the NP hard characteristic of the problem, design the genetic algorithm to solve it. Finally, use the instance to validate the method. The result reflects that the method proposed by this paper can solve the equipment maintenance tasks scheduling optimization problem, and it has good applicable value in the military domain.

ON THE HARDNESS OF RECOGNIZING BUNDLES IN TIME TABLE GRAPHS

2000 ◽  
Vol 11 (03) ◽  
pp. 467-484
Author(s):  
ANNEGRET LIEBERS ◽  
DOROTHEA WAGNER ◽  
KARSTEN WEIHE
Keyword(s):  
Directed Graph ◽  
Optimization Problem ◽  
Np Hard ◽  
Graph Theoretic ◽  
Railway Company ◽  
Railroad Network ◽  
Time Table ◽  
Np Complete

In a cooperation with the national German railway company, we construct a directed graph from a set of train time tables where train stations correspond to vertices, and where pairs of consecutive stops of trains correspond to edges. We consider the problem of locating vertices of this time table graph that intuitively correspond to train stations where the underlying railroad network branches into several directions, and that induce a partition of the edge set into bundles. We formulate this problem as a graph theoretic optimization problem, and show for two versions of the problem that they are NP-hard. For the first version we show that it is even NP-complete to decide whether any other solution besides the trival one exists.

Design, Fabrication, Experimental Analysis, and Test Flight of an Origami-Based Fixed-Wing Aerial Vehicle: µPlane

2016 ◽  
Author(s):  
Siamak G. Faal ◽  
Fuchen Chen ◽  
Weijia Tao ◽  
Shadi T. Kalat ◽  
Payam Razavi ◽  
...  
Keyword(s):  
Experimental Analysis ◽  
Optimization Problem ◽  
The Body ◽  
Flight Performance ◽  
Projection System ◽  
Outdoor Environments ◽  
Aerial Vehicle ◽  
Test Flight ◽  
Indoor And Outdoor Environments ◽  
Indoor And Outdoor

This article covers details the design, fabrication, experimental analysis, and first flight tests of μPlane, an origami-inspired aerial vehicle. μPlane is a monoplane with a straight wing planform that has a wingspan of 580 millimeters and can reach a maximum linear velocity of 6.12 meters-per-second. The body of the μPlane is fabricated by folding a single, unified crease pattern which includes all the sections required to construct the wing, tail, fuselage, and connection ports for external components, such as actuators and batteries. The wing of the plane utilizes a cambered profile to generate the required lift force. An optimization problem is formulated to find a solution to the set of constraints that provides the desired camber form. To validate the proposed design, a 3D scan of the top surface of the wing is accrued using a high-resolution fringe projection system. Finally, the flight performance and stability of μPlane are tested in both indoor and outdoor environments.

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