This paper discusses the design and implementation of a Genetic algorithm for the generation of gaits compensating for system damage on the joint level of a hexapod system. The hexapod base used for this algorithm con...
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ISBN:
(纸本)9781728180502
This paper discusses the design and implementation of a Genetic algorithm for the generation of gaits compensating for system damage on the joint level of a hexapod system. The hexapod base used for this algorithm consists of six three degree of freedom legs on a rectangular body. The purpose of this algorithm is to generate a gait such that when N motors become inoperable, as detected by the robot's internal software, the system is able to continue moving about its environment. While algorithms like this have been implemented before, the generated gaits are a sequence of discrete foot positions. This work aims to generate continuous motions profiles for each joint of the leg rather than discrete foot positions. Previous works commonly disable an entire leg when damage occurs, instead this work aims to disable only individual joint motors.
The task planning of satellite-ground time synchronization (SGTSTP) in global navigation satellite system is a complex many-objective ground station scheduling problem. In this paper, we first provide a mathematical f...
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ISBN:
(纸本)9781728121536
The task planning of satellite-ground time synchronization (SGTSTP) in global navigation satellite system is a complex many-objective ground station scheduling problem. In this paper, we first provide a mathematical formulation of the over-subscribed problem and compare with traditional scheduling problems likes job-shop scheduling problem (JSP) and satellite range scheduling problems (SRSP). In application of the Beidou Navigation System of China, with the limit of ground resource and visible time between satellites and antennas, it is no doubt a difficult problem to solve, besides, there are several objectives for SGTSTP. To solve this SGTSTP problem with efficiency and effectiveness, we propose a solving method based on decomposition-and-integration (DI), and transform SGTSTP from many-objective optimization problem (MaOPs) into a multi-objective optimization problem (MOP), to make it suitable for a multi-objective evolutionary algorithm (MOEA). Meanwhile, evolutionary many-objective optimization algorithm (EMOA) is used for original objectives as comparison. We embed the DI method into two classes of evolutionary algorithm frameworks. DI-MOEA works on a transformed two-objective version of the SGTSTP while DI-EMOA deals with the original four-objective SGTSTP problem. Computational results on two well-designed instances show that the DI-MOEA achieves worse convergence and diversity but better objective value and computational efficiency compared to the DI-EMOA.
This article deals with a performance evaluation of particle swarm optimization (PSO) and genetic algorithms (GA) for fixed order controller design. The major objective of the work is to compare the ability, computati...
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ISBN:
(纸本)9783642289613
This article deals with a performance evaluation of particle swarm optimization (PSO) and genetic algorithms (GA) for fixed order controller design. The major objective of the work is to compare the ability, computational effectiveness and efficiency to solve the optimization problem for both algorithms (PSO and GA). All simulation has been performed using a software program developed in the Matlab environment. As yet, overall results show that genetic algorithms generally can find better solutions compared to the PSO algorithm. The primary contribution of this paper is to evaluate the two algorithms in the tuning of proportional integral and derivative (PID)-controllers and minimization of cost function and maximization of robust stability in the servo system which represents a complex system. Such comparative analysis is very important for identifying both the advantages and their possible disadvantages.
Internet protocol (IP) traffic follows rules established by routing protocols. Shortest path-based protocols, such as Open Shortest Path First (OSPF), direct traffic based on arc weights assigned by the network operat...
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Internet protocol (IP) traffic follows rules established by routing protocols. Shortest path-based protocols, such as Open Shortest Path First (OSPF), direct traffic based on arc weights assigned by the network operator. Each router computes shortest paths and creates destination tables used for routing flow on the shortest paths. If a router has multiple outgoing links on shortest paths to a given destination, it splits traffic evenly over these links. It is also the role of the routing protocol to specify how the network should react to changes in the network topology, such as arc or router failures. In such situations, IP traffic is rerouted through the shortest paths not traversing the affected part of the network. This article addresses the issue of assigning OSPF weights and multiplicities to each arc, aiming to design efficient OSPF-routed networks with minimum total weighted multiplicity (multiplicity multiplied by the arc length) needed to route the required demand and handle any single arc or router failure. The multiplicities are limited to a discrete set of values, and we assume that the topology is given. We propose an evolutionary algorithm for this problem, and present results applying it to several real-world problem instances. (c) 2006 Wiley Periodicals, Inc.
A modification of Self-organizing migration algorithm for general-purpose computing on graphics processing units is proposed in this paper. The algorithm is implemented in C++ with its core parts in c-CUDA. Its implem...
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ISBN:
(纸本)9783642329210
A modification of Self-organizing migration algorithm for general-purpose computing on graphics processing units is proposed in this paper. The algorithm is implemented in C++ with its core parts in c-CUDA. Its implementation details and performance are evaluated and compared to previous, pure C++ version of algorithm. 6 commonly used artificial test functions are used to test the performance. The test results clearly show significant speed gains without a compromise in convergence quality.
The Capacitated Arc Routing Problem (CARP) is a widely investigated classic combinatorial optimization problem. Being a deterministic model, it is far away from the real world. A more practical problem model of CARP i...
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ISBN:
(纸本)9781467358910
The Capacitated Arc Routing Problem (CARP) is a widely investigated classic combinatorial optimization problem. Being a deterministic model, it is far away from the real world. A more practical problem model of CARP is the Uncertain CARP (UCARP), with the objective of finding a robust solution which performs well in all possible environments. There exist few algorithms for UCARP in previous work. In this paper, a Memetic algorithm (MA) and its modified version in time consumption for UCARP are proposed. Experimental results on two benchmark test sets show that with an integrated fitness function and a large step-size local search operator, the new MAs show excellent ability to find robust solutions for UCARP. We also present a less time-consuming version of our MA which shows significant advantages in time consumption.
Surrogate models of fitness have been presented as a way of reducing the number of fitness evaluations required by an evolutionary algorithm. This is of particular interest with expensive fitness functions where the c...
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ISBN:
(纸本)9781424481262
Surrogate models of fitness have been presented as a way of reducing the number of fitness evaluations required by an evolutionary algorithm. This is of particular interest with expensive fitness functions where the cost of building the model is outweighed by the saving of using fewer function evaluations. In this paper we show how a Markov network model can be used as a surrogate fitness function in a genetic algorithm. We demonstrate this applied to a number of well-known benchmark functions and although the results are good in terms of function evaluations the model-building overhead requires a substantially more expensive fitness function to be worthwhile. We move on to describe a fitness function for feature selection in Case-Based Reasoning, which is considerably more expensive than the other benchmark functions we used. We show that for this problem using the surrogate offers a significant decrease in total run time compared to a GA using the true fitness function.
This paper proposes a multiobjective optimization approach for designing selected coupled-field models. The optimization method is based on evolutionary algorithm (EA). Proposed technique overtakes one of the most pop...
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ISBN:
(纸本)9788494140761
This paper proposes a multiobjective optimization approach for designing selected coupled-field models. The optimization method is based on evolutionary algorithm (EA). Proposed technique overtakes one of the most popular multiobjective evolutionary algorithm NSGAII [5,6] on several benchmark and engineering problems. Coupling between electrical, thermal and mechanical fields is considered. Finite element method (FEM) is used to simulate direct coupled problems numerically. The software packages based on FEM are adapted to create the optimization system. Suitable interfaces between optimization algorithm and the FEM software are created. They use internal script languages embedded in preprocesors of the FEM systems. Different types of functionals are formulated on the basis of the results obtained from coupled-field analysis. Functionals depending on the volume of the structure are also proposed. Parametric NURBS curves are used to model some optimized structures. Numerical examples for bi-objective and three-objective optimization problems are presented.
A stand-alone metaheuristic based algorithm can solve a specific optimal control problem. The result is a quasi-optimal solution that is a sequence of values assigned to control inputs over the control horizon. Howeve...
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ISBN:
(纸本)9781728198095
A stand-alone metaheuristic based algorithm can solve a specific optimal control problem. The result is a quasi-optimal solution that is a sequence of values assigned to control inputs over the control horizon. However, this solution can be used only by an open-loop system. This paper proposes a method to achieve a closed-loop control structure able to control the dynamic system optimally, using the quasi-optimal state trajectory constructed through the metaheuristic based algorithm.
In this paper, we present a new unfalsified adaptive control algorithm. This algorithm leads to a real-time controller tuning method. The algorithm consists of two main elements: 1) Switching of controllers in a contr...
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ISBN:
(纸本)9781457711039
In this paper, we present a new unfalsified adaptive control algorithm. This algorithm leads to a real-time controller tuning method. The algorithm consists of two main elements: 1) Switching of controllers in a controller set by the epsilon-hysteresis switching algorithm and 2) Optimization of the controller set via an evolutionary algorithm (EA). The real-time controller tuning is demonstrated for a nonminimum-phase continuous stirred tank reactor (CSTR) model.
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