Three dimensional integrated circuits (3D ICs) can alleviate the problem of interconnection, a critical problem in the nanoscale era, and are also promising for heterogeneous integration. This paper proposes a two-pha...
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Three dimensional integrated circuits (3D ICs) can alleviate the problem of interconnection, a critical problem in the nanoscale era, and are also promising for heterogeneous integration. This paper proposes a two-phase method combining the ant system algorithm (AS) and simulated annealing (SA) to handle 3D IC floorplanning with fixed-outline constraints. In the first AS phase, the floorplans are constructed by sequentially packing the block one by one, and the AS is used to explore the appropriate packing order and device layer assignment for the blocks. When packing a block, a proper position including the coordinates and the appropriate layer in the partially constructed floorplan should be chosen from all possible positions. While packing the blocks, a probability layer assignment strategy is proposed to determine the device layer assignment of unpacked blocks. After the AS phase, the SA phase is used to perform further optimization. The proposed method can also be easily applied to 2D floorplanning problems. Compared with the state of the art 3D/2D fixed-outline floorplanner, the experimental results demonstrate the effectiveness of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.
This paper discusses the methodology used in the development of advanced traveller information system (ATIS). This system is designed as a part of web geographical information system (GIS) based advanced public transp...
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This paper discusses the methodology used in the development of advanced traveller information system (ATIS). This system is designed as a part of web geographical information system (GIS) based advanced public transport systems. Web GIS-based ATIS system includes spatial data for the designed functionalities and provides GIS capabilities to the users through the internet. In addition to these functionalities, a route planning algorithm to plan the shortest route between the selected bus transit points is also designed using ant system algorithm and is integrated with web GIS. This study presents the ant system algorithm adopted for the shortest route finding with the methodology developed for the web GIS-based ATIS system for the study area of the city Chandigarh in India using open source software MapServer as web map server. This study also discusses the three-tier logical architecture used in the methodology for providing GIS capabilities to the user over the internet.
Intrinsically, the attainment of optimal solution via the ant Colony system (ACS) algorithm essentially depends on the attractiveness of the quantity of pheromone on a given path. This leads to neglecting the velocity...
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Intrinsically, the attainment of optimal solution via the ant Colony system (ACS) algorithm essentially depends on the attractiveness of the quantity of pheromone on a given path. This leads to neglecting the velocity of the ant which constitutes an important nature-based heuristic information. The aim of this paper is to improve an existing ACS algorithm by integrating ant velocity, an insight gained from the Intelligent Water Drops (IWD) algorithm. A bi-objective model was formulated and adapted into the proposed ACS algorithm to optimize route length and social cost associated with various activities along the route. The solution technique was based on the min-max approach. A 14-node road network data, measuring distances and social costs was used in validating the algorithm. Both the benchmark algorithm and our proposed ant velocity-based ACS algorithm yielded the same bi-optimal solution (12 km, GHS 7) of distance and social cost along the path 1 -> 4 -> 7 -> 11 -> 12 -> 14. The proposed ACS algorithm converges at the 127th iteration, corresponding to approximately 3 s execution time. Obviously, the proposed ACS algorithm outperforms the benchmark algorithm which converges at the 207th iteration, with approximately 5 s execution time. Therefore, the proposed ACS algorithm has outperformed the benchmark ACS algorithm in respect of time (or the number of iterations needed for convergence) by approximately 39 %. Evidently, with a velocity of 0.2445 ms-2, the optimal time taken by the best ant to complete the tour is approximately 27 s.
Running- time analysis of ant colony optimization (ACO) is crucial for understanding the power of the algorithm in computation. This paper conducts a running-time analysis of ant system algorithms (AS) as a kind of AC...
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Running- time analysis of ant colony optimization (ACO) is crucial for understanding the power of the algorithm in computation. This paper conducts a running-time analysis of ant system algorithms (AS) as a kind of ACO for traveling salesman problems (TSP). The authors model the AS algorithm as an absorbing Markov chain through jointly representing the best-so-far solutions and pheromone matrix as a discrete stochastic status per iteration. The running-time of AS can be evaluated by the expected first-hitting time (FHT), the least number of iterations needed to attain the global optimal solution on average. The authors derive upper bounds of the expected FHT of two classical AS algorithms (i.e., ant quantity system and ant-cycle system) for TSP. They further take regular-polygon TSP (RTSP) as a case study and obtain numerical results by calculating six RTSP instances. The RTSP is a special but real-world TSP where the constraint of triangle inequality is stringently imposed. The numerical results derived from the comparison of the running time of the two AS algorithms verify our theoretical findings.
ant colony optimisation (ACO) which is one of the most popular algorithms in machine learning has been used widely to solve combinatorial optimisation problems. However, there are few studies for its runtime analysis ...
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ant colony optimisation (ACO) which is one of the most popular algorithms in machine learning has been used widely to solve combinatorial optimisation problems. However, there are few studies for its runtime analysis which can reflect the computational complexity of ACO algorithm. The presented paper proposes a method for analysing the convergence time of ant system algorithm with pheromone rate. The analysis is a process of estimating the iteration time that pheromone rate attains the objective value and the mean convergence time based on the objective pheromone rate in expectation. The proposed method can be used to analyse the computational complexity of other ACO algorithms. Finally, a brief ant system algorithm is analysed as an example of using the method.
When executing a complex mission, the multi-AUV system need to confirm a better task allocation scheme to make sure that the system is efficient. However, there are many standards which are utilized to determine the s...
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ISBN:
(纸本)9781509023967
When executing a complex mission, the multi-AUV system need to confirm a better task allocation scheme to make sure that the system is efficient. However, there are many standards which are utilized to determine the system's efficient, and there maybe confliction between them. In order to solve the task allocation of multi-AUV system based on multi-objective optimization, a multi-objective optimization based on ant system algorithm was proposed. By the single-objective optimization in single antsystem and the interaction between different ants systems, this algorithm achieve the Pareto solution's set at last. On the other hand, an algorithm evaluation method was given out to evaluate the performance of the algorithm above. Based on this algorithm, the task allocation of multi-AUV system based on multi-objective optimization was studied in details and the stimulation of task allocation was provided.
The paper presents an antsystem based algorithm to optimally plan multi-gravity assist trajectories. The algorithm is designed to solve planning problems in which there is a strong dependency of one decision on all t...
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ISBN:
(纸本)9781424481262
The paper presents an antsystem based algorithm to optimally plan multi-gravity assist trajectories. The algorithm is designed to solve planning problems in which there is a strong dependency of one decision on all the previously made decisions. In the case of multi-gravity assist trajectory planning, the number of possible paths grows exponentially with the number of planetary encounters. The proposed algorithm avoids scanning all the possible paths and provides good results at a low computational cost. The algorithm builds the solution incrementally according to antsystem paradigms. Unlike standard ACO, at every planetary encounter, each ant makes a decision based on the information stored in a tabu and feasible list. The approach demonstrated to be competitive, on a number of instances of a real trajectory design problem, against known GA and PSO algorithms
作者：
Rui YangEAIC Dept
China Waterborne Transportation Institute Beijing China
This paper aimed to optimize the technique parameters of tracking buoy by a hydrodynamic method through an experiment on the sea. A survey was created based on the study of technical characters of oil spill tracking b...
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This paper aimed to optimize the technique parameters of tracking buoy by a hydrodynamic method through an experiment on the sea. A survey was created based on the study of technical characters of oil spill tracking buoy to achieve an allweather whole procedure monitoring propose for oil spill by using of satellite positioning communication mode, which can provide an effective technical method for the rapid response of oil spill emergency.
This paper presents investigations into modeling and active vibration control (AVC) of a flexible plate structure using continuous ant system algorithm (CASA) such structures. The optimization technique is utilized to...
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ISBN:
(纸本)9781424453450
This paper presents investigations into modeling and active vibration control (AVC) of a flexible plate structure using continuous ant system algorithm (CASA) such structures. The optimization technique is utilized to obtain a dynamic model of a flexible plate structure based on auto-regressive with exogenous (ARX) input model structure. The flexible plate structure is subjected to two different disturbance signal types, namely random, and finite duration step. The fitness function for the CASA is the mean-squared error (MSE) between the measured and estimated outputs of the plate. The validation of the algorithm is presented in both time and frequency domains. The developed CASA modeling approach is used for AVC system design to suppress the vibration of the flexible plate. The performance of the controller is assessed in terms of level of attenuation achieved in the power spectral density of the observed signal.
This paper presents an algorithm that is based on antsystem to solve the course timetabling problem. The problem is modeled using the bipartite graph. Four heuristic factors are derived from the graph characteristic,...
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ISBN:
(纸本)9781424447350
This paper presents an algorithm that is based on antsystem to solve the course timetabling problem. The problem is modeled using the bipartite graph. Four heuristic factors are derived from the graph characteristic, are used to direct ants as the agent in finding course timetable elements. The concept of negative pheromone was also applied to ensure that paths leading to dead ends are not chosen. The performance of this proposed algorithm is promising when comparison of performance was made with the original ant system algorithm.
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