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In the area of applied optimisation, heuristics are a popular means to address computational problems of high complexity. Modelling the problem and mapping all variations of its solution into a so-called solution space are integral parts of this process. Representing solutions as graphs is common and, for a special type of graph, Prüfer Code (PC) offers a computationally efficient mapping (algorithms...
In context of human-machine-interaction trajectories need to be rerouted or re-planned with reduced dynamical constraints in order to avoid collisions. This requires online feasible algorithm for trajectory planning in space. In this paper a new method for planning time-optimal trajectories subject to dynamic and geometrical constraints is proposed. Distinctively to other work, both spatial and temporal...
The Information-Centric Network (ICN) is very promising in the area of Complex Active Networks (CANs), where the data-centric approach is useful in reducing the data retrieval latency as well as the network traffic of active networking services. Also, the in-network caching and processing capabilities in ICN limits the massive data access to the data producers and so relaxes the need of continuous...
We are interested in an easy combinatorial optimization problem having several applications in the real world, namely the matrix chain product problem that may be solved by a well known dynamic programming algorithm (DPA). Our contribution is two-fold. It first consists in the design of an approach based on the DPA for the determination of multiple optimal solutions i.e. optimal parenthesizations...
The importance of using heuristics in an optimization algorithm is well established, particularly in solving complex real-world problems. It is then expected that users know certain key problem information a priori and are able to implement the information in a suitable optimization algorithm. However, in many problems, such problem information may not be available before an optimization task is performed,...
The scalability of optimization algorithms is an important issue that has been thoroughly studied in the past. However, these studies were normally conducted by gradually increasing the dimensionality of the benchmark and analyzing how an algorithm exhibiting a good performance on low-dimensional problems degrades as the problem size increases. In this contribution we follow the opposite approach:...
The management of complex network services requires flexible and efficient service provisioning as well as optimized handling of continuous changes in the workload of the services. To adapt to changes in the demand, service components need to be replicated (scaling) and allocated to physical resources (placement) dynamically. In this paper, we propose a fully automated approach to the joint optimization...
We consider a class of mixed integer programs where the problem is convex except for a vector of discrete variables. Two methods based on the Alternating Direction Method of Multipliers (ADMM) are presented. The first, which has appeared in the recent literature, duplicates the discrete variable, with one copy allowed to vary continuously. This results in a simple projection, or rounding, to determine...
Performance optimization for mapreduce computing in Hadoop platform is a tedious yet challenging problem due to the complexity of system organization with an extensive list of configuration parameters to be considered. In order to address and resolve this problem, various parameter optimization algorithms are proposed in this research from a naive exhaustive method to a random and a couple of heuristically-based...
Many applications supported by the crowdsourcing are subject to delay constraints, and a real time result returned with a better partial fulfillment is preferable to the complement with delay latency. However, existing task assignment algorithms that only consider the case of full completion may not perform well. In this paper, we investigate the optimal online task assignment without knowledge about...
Dynamic programming is a popular optimization technique, developed in the 60's and still widely used today in several fields for its ability to find global optimum. Dynamic Programming Algorithms (DPAs) can be developed in many dimension. However, it is known that if the DPA dimension is greater or equal to two, the algorithm is an NP complete problem. In this paper we present an approximation of...
It is natural way to write Chinese characters by digital pen for foreign students, whose handwriting information is much richer than digital image. Stroke matching is the prerequisite to analyze handwriting errors of Chinese character. Present research hardly delivers the optimal solution of the problem on the growing sizes and complexity because of wide differences among learners' writing qualities...
Global alignment of two protein-protein interaction networks is an essentially important task in bioinformatics/computational biology field of study. It is a challenging and widely studied research topic in recent years. Accurately aligned networks allow us to identify functional modules of proteins and/or orthologous proteins from which unknown functions of a protein can be inferred. We here introduce...
In this study several algorithms for the generation of inexpensive and fault-tolerant graphs are evaluated with respect to the quality of the found graphs and to the runtime requirements. A special focus lies on the properties of the algorithm that basically is a simulation of the foraging of the slime mold Physarum polycephalum, since in many other works the deployment of this algorithm does not...
Voltage regulation is critical for distribution systems, and has become a much more challenging problem with the increasing proliferation of distributed renewable energy resources that cause frequent and rapid voltage fluctuations beyond what can be handled by the traditional voltage regulation methods. In this paper, motivated by the shortcomings of two previously proposed inverter-based local volt/var...
We address the problem of detecting and mitigating the effect of malicious attacks on the sensors of a linear dynamical system. We develop a novel, efficient algorithm that uses a Satisfiability Modulo Theory approach to isolate the compromised sensors and estimate the system state despite the presence of the attack, thus harnessing the intrinsic combinatorial complexity of the problem. Simulation...
Under the guidance of scientific and technological innovation concept, new technology and algorithms are applied to information retrieval and real estate registration system. These excellent algorithms and hardware technology make our file management more convenient, intelligent, and efficient. In this paper, researches on the establishment of intelligent file management system and document retrieval...
We consider the state space explosion problem which is a fundamental obstacle in formal verification of critical systems. In this paper, we propose a fast algorithm for distributing state spaces on a network of workstations. Our solution is an improvement version of SSCGDA algorithm (for Strict Strong Coloring based Graph Distribution Algorithm) which introduced the coloring concept and dominance...
The Game of the Amazons is a two-player abstract territory game. It has attracted attention in game research because of its simple rules and its complexity of play. A number of Amazons-playing programs have emerged in recent years. Different search algorithms are used in Amazons programs. Minimax is one of the most commonly used Amazons search algorithms. It is usually optimized with augmentations,...
Regulating the power consumption to avoid peaks in demand is a common practice. Demand Response(DR) is being used by utility providers to minimize costs or ensure system reliability. Although it has been used extensively there is a shortage of solutions dealing with dynamic DR. Past attempts focus on minimizing the load demand without considering the sustainability of the reduced energy. In this paper...
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