Search results for: traveling salesman problem.

Authors: Gideon Avigad, Amiram Moshaiov, Neima Brauner

Abstract:

An IEC technique is described for a multi-objective search of conceptual solutions. The survivability of solutions is influenced by both model-based fitness and subjective human preferences. The concepts- preferences are articulated via a hierarchy of sub-concepts. The suggested method produces an objectivesubjective front. Academic example is employed to demonstrate the proposed approach.

Keywords: Conceptual solution, engineering design, hierarchical planning, multi-objective search, problem reduction.

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Authors: Xun Liang

Abstract:

In this paper, we probe into the traffic assignment problem by the chromosome-learning-based path finding method in simulation, which is to model the driver' behavior in the with-in-a-day process. By simply making a combination and a change of the traffic route chromosomes, the driver at the intersection chooses his next route. The various crossover and mutation rules are proposed with extensive examples.

Keywords: Chromosome learning, crossover, mutation, traffic path finding.

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Authors: Aurelija Burinskienė, Dalė Dzemydienė, Arūnas Miliauskas

Abstract:

This research aims at developing the approach for more effective freight delivery and transportation process management. The road congestions and the identification of causes are important, as well as the context information recognition and management. The measure of many parameters during the transportation period and proper control of driver work became the problem. The number of vehicles per time unit passing at a given time and point for drivers can be evaluated in some situations. The collection of data is mainly used to establish new trips. The flow of the data is more complex in urban areas. Herein, the movement of freight is reported in detail, including the information on street level. When traffic density is extremely high in congestion cases, and the traffic speed is incredibly low, data transmission reaches the peak. Different data sets are generated, which depend on the type of freight delivery network. There are three types of networks: long-distance delivery networks, last-mile delivery networks and mode-based delivery networks; the last one includes different modes, in particular, railways and other networks. When freight delivery is switched from one type of the above-stated network to another, more data could be included for reporting purposes and vice versa. In this case, a significant amount of these data is used for control operations, and the problem requires an integrated methodological approach. The paper presents an approach for providing e-services for drivers by including the assessment of the multi-component infrastructure needed for delivery of freights following the network type. The construction of such a methodology is required to evaluate data flow conditions and overloads, and to minimize the time gaps in data reporting. The results obtained show the possibilities of the proposing methodological approach to support the management and decision-making processes with functionality of incorporating networking specifics, by helping to minimize the overloads in data reporting.

Keywords: Transportation networks, freight delivery, data flow, monitoring, e-services.

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Authors: M. R. Rouhi, S. Shafiei, A. Taghavipour, H. Adibi-Asl, A. Doosthoseini

Abstract:

This research targets at alleviating the problem of range anxiety associated with the battery electric vehicles (BEVs) by considering mechanical and control aspects of the powertrain. In this way, all the energy consuming components and their effect on reducing the range of the BEV and battery life index are identified. On the other hand, an appropriate control strategy is designed to guarantee the performance of the BEV and the extended electric range which is evaluated by an extensive simulation procedure and a real-world driving schedule.

Keywords: Battery, electric vehicles EV, ultra-capacitor.

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Authors: Mohammed Meziani, Pierre-Louis Cayrel

Abstract:

In this paper we propose two first non-generic constructions of multisignature scheme based on coding theory. The first system make use of the CFS signature scheme and is secure in random oracle while the second scheme is based on the KKS construction and is a few times. The security of our construction relies on a difficult problems in coding theory: The Syndrome Decoding problem which has been proved NP-complete [4].

Keywords: Post-quantum cryptography, Coding-based cryptography, Digital signature, Multisignature scheme.

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Authors: Jiří Barta, Tomáš Ludík, Jiří Urbánek

Abstract:

Topics Disaster and Emergency Management are highly debated among experts. Fast communication will help to deal with emergencies. Problem is with the network connection and data exchange. The paper suggests a solution, which allows possibilities and perspectives of new flexible communication platform to the protection of communication systems for crisis management. This platform is used for everyday communication and communication in crisis situations too.

Keywords: Communication Platform, Crisis Management, Crisis Communication, Information Systems, Interoperability, Security Environment.

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Authors: Y. Shpungin

Abstract:

Estimating the lifetime distribution of computer networks in which nodes and links exist in time and are bound for failure is very useful in various applications. This problem is known to be NP-hard. In this paper we present efficient combinatorial approaches to Monte Carlo estimation of network lifetime distribution. We also present some simulation results.

Keywords: Combinatorial spectrum, Monte Carlo, Networklifetime, Unreliable nodes and edges.

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Authors: Konstantinos Liagkouras, Konstantinos Metaxiotis

Abstract:

In this paper we present a classification of the various technologies applied for the solution of the portfolio selection problem according to the discipline and the methodological framework followed. We provide a concise presentation of the emerged categories and we are trying to identify which methods considered obsolete and which lie at the heart of the debate. On top of that, we provide a comparative study of the different technologies applied for efficient portfolio construction and we suggest potential paths for future work that lie at the intersection of the presented techniques.

Keywords: Portfolio selection, optimization techniques, financial models, stochastics, heuristics.

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Authors: A. K. Kamath, N. M. Singh, R. Pasumarthy

Abstract:

This paper investigates the control of a bouncing ball using Model Predictive Control. Bouncing ball is a benchmark problem for various rhythmic tasks such as juggling, walking, hopping and running. Humans develop intentions which may be perceived as our reference trajectory and tries to track it. The human brain optimizes the control effort needed to track its reference; this forms the central theme for control of bouncing ball in our investigations.

Keywords: Bouncing Ball, impact dynamics, intermittent control, model predictive control.

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Authors: Krishna S. Raghuwaiya, Shonal Singh, Jito Vanualailai

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In this paper, we study the formation control problem for car-like mobile robots. A team of nonholonomic mobile robots navigate in a terrain with obstacles, while maintaining a desired formation, using a leader-following strategy. A set of artificial potential field functions is proposed using the direct Lyapunov method for the avoidance of obstacles and attraction to their designated targets. The effectiveness of the proposed control laws to verify the feasibility of the model is demonstrated through computer simulations

Keywords: Control, Formation, Lyapunov, Nonholonomic

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Authors: K. A. Laptinskiy, S. A. Burikov, A. M. Vervald, S. A. Dolenko, T. A. Dolenko

Abstract:

The article presents the results of the application of artificial neural networks to separate the fluorescent contribution of nanodiamonds used as biomarkers, adsorbents and carriers of drugs in biomedicine, from a fluorescent background of own biological fluorophores. The principal possibility of solving this problem is shown. Use of neural network architecture let to detect fluorescence of nanodiamonds against the background autofluorescence of egg white with high accuracy - better than 3 ug/ml.

Keywords: Artificial neural networks, fluorescence, data aggregation.

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Authors: Li Feng

Abstract:

We investigate the planar quasi-septic non-analytic systems which have a center-focus equilibrium at the origin and whose angular speed is constant. The system could be changed into an analytic system by two transformations, with the help of computer algebra system MATHEMATICA, the conditions of uniform isochronous center are obtained.

Keywords: Non-analytic, center–focus problem, Lyapunov constant, uniform isochronous center.

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Authors: Miaomiao Yang, Shouming Zhong

Abstract:

This paper studies the problem of asymptotically stability for neural networks with time-varying delays.By establishing a suitable Lyapunov-Krasovskii function and several novel sufficient conditions are obtained to guarantee the asymptotically stability of the considered system. Finally,two numerical examples are given to illustrate the effectiveness of the proposed main results.

Keywords: Neural networks, Lyapunov-Krasovskii, Time-varying delays, Linear matrix inequality.

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Authors: H. Y. Jung, Ju H. Park, S. M. Lee

Abstract:

Sampled-data controller is presented for solid oxide fuel cell systems which is expressed by a sector bounded nonlinear model. The proposed control law is obtained by solving a convex problem satisfying several linear matrix inequalities. Simulation results are given to show the effectiveness of the proposed design method.

Keywords: Sampled-data control, Sector bound, Solid oxide fuel cell, Time-delay.

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Authors: Timothee G. Leleu

Abstract:

A new technique of topological multi-scale analysis is introduced. By performing a clustering recursively to build a hierarchy, and analyzing the co-scale and intra-scale similarities, an Iterated Function System can be extracted from any data set. The study of fractals shows that this method is efficient to extract self-similarities, and can find elegant solutions the inverse problem of building fractals. The theoretical aspects and practical implementations are discussed, together with examples of analyses of simple fractals.

Keywords: hierarchical clustering, multi-scale analysis, Similarity hashing.

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Authors: Gianpaolo Ghiani, Emanuela Guerriero, Emanuele Manni, Alessandro Romano

Abstract:

In this article, we deal with a variant of the classical course timetabling problem that has a practical application in many areas of education. In particular, in this paper we are interested in high schools remedial courses. The purpose of such courses is to provide under-prepared students with the skills necessary to succeed in their studies. In particular, a student might be under prepared in an entire course, or only in a part of it. The limited availability of funds, as well as the limited amount of time and teachers at disposal, often requires schools to choose which courses and/or which teaching units to activate. Thus, schools need to model the training offer and the related timetabling, with the goal of ensuring the highest possible teaching quality, by meeting the above-mentioned financial, time and resources constraints. Moreover, there are some prerequisites between the teaching units that must be satisfied. We first present a Mixed-Integer Programming (MIP) model to solve this problem to optimality. However, the presence of many peculiar constraints contributes inevitably in increasing the complexity of the mathematical model. Thus, solving it through a general-purpose solver may be performed for small instances only, while solving real-life-sized instances of such model requires specific techniques or heuristic approaches. For this purpose, we also propose a heuristic approach, in which we make use of a fast constructive procedure to obtain a feasible solution. To assess our exact and heuristic approaches we perform extensive computational results on both real-life instances (obtained from a high school in Lecce, Italy) and randomly generated instances. Our tests show that the MIP model is never solved to optimality, with an average optimality gap of 57%. On the other hand, the heuristic algorithm is much faster (in about the 50% of the considered instances it converges in approximately half of the time limit) and in many cases allows achieving an improvement on the objective function value obtained by the MIP model. Such an improvement ranges between 18% and 66%.

Keywords: Heuristic, MIP model, Remedial course, School, Timetabling.

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Authors: Lei Wang, Sizong Guo

Abstract:

In this paper, we study the numerical method for solving second-order fuzzy differential equations using Adomian method under strongly generalized differentiability. And, we present an example with initial condition having four different solutions to illustrate the efficiency of the proposed method under strongly generalized differentiability.

Keywords: Fuzzy-valued function, fuzzy initial value problem, strongly generalized differentiability, adomian decomposition method.

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Authors: Ahmed Nouainia, Mohamed Hajji, Taoufik Aguili

Abstract:

In this paper, an electromagnetic analysis is presented for describing the influence of shielding in a rectangular waveguide. A hybridization based on the method of moments combined to the generalized equivalent circuit MoM-GEC is used to model the problem. This is validated by applying the MoM-GEC hybridization to investigate a diffraction structure. It consists of electromagnetic diffraction by an iris in a rectangular waveguide. Numerical results are shown and discussed and a comparison with FEM and Marcuvitz methods is achieved.

Keywords: Inductive irises, MoM-GEC, waveguide, shielding.

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Authors: Jan Zeman

Abstract:

The paper describes the futures trading and aims to design the speculators trading strategy. The problem is formulated as the decision making task and such as is solved. The solution of the task leads to complex mathematical problems and the approximations of the decision making is demanded. Two kind of approximation are used in the paper: Monte Carlo for the multi-step prediction and iteration spread in time for the optimization. The solution is applied to the real-market data and the results of the off-line experiments are presented.

Keywords: futures trading, decision making

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

Abstract:

We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: Autonomous surveillance, Bayesian reasoning, decision-support, interventions, patterns-of-life, predictive analytics, predictive insights.

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Authors: A. Schuster

Abstract:

Many artificial intelligence (AI) techniques are inspired by problem-solving strategies found in nature. Robustness is a key feature in many natural systems. This paper studies robustness in artificial neural networks (ANNs) and proposes several novel, nature inspired ANN architectures. The paper includes encouraging results from experimental studies on these networks showing increased robustness.

Keywords: robustness, robust artificial neural networks architectures.

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Authors: Adil AL-Rammahi

Abstract:

In this short paper, new properties of transition matrix were introduced. Eigen values for small order transition matrices are calculated in flexible method. For benefit of these properties applications of these properties were studied in the solution of Markov's chain via steady state vector, and information theory via channel entropy. The implemented test examples were promised for usages.

Keywords: Eigen value problem, transition matrix, state vector, information theory.

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Authors: Yasar Guneri Sahin, Mehmet Cudi Okur

Abstract:

Assessment of IEP (Individual Education Plan) is an important stage in the area of special education. This paper deals with this problem by introducing computer software which process the data gathered from application of IEP. The software is intended to be used by special education institution in Turkey and allows assessment of school and family trainings. The software has a user friendly interface and its design includes graphical developer tools.

Keywords: Disabled individual, software for education, assessment of education, special education.

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Authors: Haiyan Wang

Abstract:

Many researchers have been discussing the importance of language input in second language acquisition. The author holds that the bigger problem lies in how to activate language learners' language knowledge and raise their language output consciousness and competence. Analyzing the importance of language output based on theory and reality, this paper mainly explores the essence of language output and its revelation for second language acquisition in order to make second language learners really raise their communicative competence.

Keywords: Language output, second language acquisition, communicative competence.

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Authors: P. Luangpaiboon

Abstract:

Various intelligences and inspirations have been adopted into the iterative searching process called as meta-heuristics. They intelligently perform the exploration and exploitation in the solution domain space aiming to efficiently seek near optimal solutions. In this work, the bee algorithm, inspired by the natural foraging behaviour of honey bees, was adapted to find the near optimal solutions of the transportation management system, dynamic multi-zone dispatching. This problem prepares for an uncertainty and changing customers- demand. In striving to remain competitive, transportation system should therefore be flexible in order to cope with the changes of customers- demand in terms of in-bound and outbound goods and technological innovations. To remain higher service level but lower cost management via the minimal imbalance scenario, the rearrangement penalty of the area, in each zone, including time periods are also included. However, the performance of the algorithm depends on the appropriate parameters- setting and need to be determined and analysed before its implementation. BEE parameters are determined through the linear constrained response surface optimisation or LCRSOM and weighted centroid modified simplex methods or WCMSM. Experimental results were analysed in terms of best solutions found so far, mean and standard deviation on the imbalance values including the convergence of the solutions obtained. It was found that the results obtained from the LCRSOM were better than those using the WCMSM. However, the average execution time of experimental run using the LCRSOM was longer than those using the WCMSM. Finally a recommendation of proper level settings of BEE parameters for some selected problem sizes is given as a guideline for future applications.

Keywords: Meta-heuristic, Bee Algorithm, Dynamic Multi-Zone Dispatching, Linear Constrained Response SurfaceOptimisation Method, Weighted Centroid Modified Simplex Method

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Authors: Satoshi Shimizu, Kazuaki Yamaguchi, Toshiki Saitoh, Sumio Masuda

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Some fast exact algorithms for the maximum weight clique problem have been proposed. Östergard’s algorithm is one of them. Kumlander says his algorithm is faster than it. But we confirmed that the straightforwardly implemented Kumlander’s algorithm is slower than O¨ sterga˚rd’s algorithm. We propose some improvements on Kumlander’s algorithm.

Keywords: Maximum weight clique, exact algorithm, branch-andbound, NP-hard.

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Authors: Imane El Karaoui, Mohammed Maaroufi, Hamid Chaikhy

Abstract:

Doubly Fed Induction Generator (DFIG) is one of the most reliable wind generator. Major problem in wind power generation is to generate Sinusoidal signal with very low THD on variable speed caused by inverter two levels used. This paper presents a multi-level inverter whose objective is to reduce the THD and the dimensions of the output filter. This work proposes a three-level NPC-type inverter, the results simulation are presented demonstrating the efficiency of the proposed inverter.

Keywords: DFIG, multilevel inverter, NPC inverter , THD, Induction machine.

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Authors: Zhengnan Shi

Abstract:

In this paper, we consider the problem of Popular Matching of strictly ordered preference lists. A Popular Matching is not guaranteed to exist in any network. We propose an IDbased, constant space, self-stabilizing algorithm that converges to a Maximum Popular Matching an optimum solution, if one exist. We show that the algorithm stabilizes in O(n5) moves under any scheduler (daemon).

Keywords: self-stabilization, popular matching, algorithm, distributed computing, fault tolerance

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Authors: Yue Zhao, Jianping Li

Abstract:

This paper covers the present situation and problem of experimental teaching of mathematics specialty in recent years, puts forward and demonstrates experimental teaching methods for different education. From the aspects of content and experimental teaching approach, uses as an example the course “Experiment for Program Designing & Algorithmic Language" and discusses teaching practice and laboratory course work. In addition a series of successful methods and measures are introduced in experimental teaching.

Keywords: Differentiated teaching, experimental teaching, program design and algorithmic language, teaching method.

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Authors: Firas Daghistani, Hossam Abuel Naga

Abstract:

Waste tyres is an ongoing global problem that has a negative effect on the environment. Waste tyres are discarded in stockpiles where they provide harm to the environment in many ways. Finding applications to these materials can help in reducing this global problem. One of these applications is recycling these waste materials and using them in geotechnical engineering. Recycled waste tyre particulates can be mixed with sand to form a lightweight material with varying shear strength characteristics. This research further investigates the inclusion of particulate rubber to sand and whether it can increase or decrease the shear strength characteristics of the mixture. For the experiment, a series of direct shear tests was performed on a poorly graded sand with a mean particle size of 0.32 mm mixed with recycled poorly graded particulate rubber with a mean particle size of 0.51 mm. The shear tests were performed on four normal stresses 30, 55, 105, 200 kPa at a shear rate of 1 mm/minute. Different percentages of particulate rubber content were used in the mixture i.e., 10%, 20%, 30% and 50% of sand dry weight at three density states namely loose, slight dense, and dense state. The size ratio of the mixture, which is the mean particle size of the particulate rubber divided by the mean particle size of the sand, was 1.59. The results identified multiple parameters that can influence the shear strength of the mixture. The parameters were: normal stress, particulate rubber content, mixture gradation, mixture size ratio, and the mixture’s density. The inclusion of particulate rubber to sand showed a decrease to the internal friction angle, and an increase to the apparent cohesion. Overall, the inclusion of particulate rubber did not have a significant influence on the shear strength of the mixture. For all the dense states at the low normal stresses 30, and 55 kPa, the inclusion of particulate rubber showed a slight increase in the shear strength where the peak was at 20-30% rubber content of the sand’s dry weight. On the other hand, at the high normal stresses 105, and 200 kPa, there was a slight decrease in the shear strength.

Keywords: Direct shear, granular material, sand-rubber mixture, shear strength, waste material.

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