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A reliable affine relaxation method for global optimization

4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH 2015年第3期13卷 247-277页

作者： Ninin, Jordan Messine, Frederic Hansen, Pierre ENSTA Bretagne LabSTICC IHSEV Team F-29806 Brest France ENSEEIHT IRIT F-31071 Toulouse France HEC Montreal Studies & Res Decis Anal Montreal PQ Canada Ecole Polytech LIX Palaiseau France

An automatic method for constructing linear relaxations of constrained global optimization problems is proposed. Such a construction is based on affine and interval arithmetics and uses operator overloading. These linear programs have exactly the same numbers of variables and inequality constraints as the given problems. Each equality constraint is replaced by two inequalities. This new procedure for computing reliable bounds and certificates of infeasibility is inserted into a classical branch and bound algorithm based on interval analysis. Extensive computation experiments were made on 74 problems from the COCONUT database with up to 24 variables or 17 constraints;61 of these were solved, and 30 of them for the first time, with a guaranteed upper bound on the relative error equal to . Moreover, this sample comprises 39 examples to which the GlobSol algorithm was recently applied finding reliable solutions in 32 cases. The proposed method allows solving 31 of these, and 5 more with a CPU-time not exceeding 2 min.

关键词： Affine arithmetic Interval analysis Linear relaxation branch and bound algorithm Global optimization

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Mining scheduling knowledge for job shop scheduling problem 15

Mining scheduling knowledge for job shop scheduling problem

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15th IFAC Symposium on Information Control Problems in Manufacturing

作者： Wang, C. L. Rong, G. Weng, W. Feng, Y. P. Zhejiang Univ Inst Cyber Syst & Control State Key Lab Ind Control Technol Hangzhou 310003 Zhejiang Peoples R China Waseda Univ Grad Sch Informat Prod & Syst Wakamatsu Ku Kitakyushu Fukuoka 8080135 Japan

The optimal or near-optimal schedules generated by traditional optimization or approximation methods for job shop scheduling problems (JSSP) contain valuable scheduling patterns about this kind of scheduling problems. These patterns could be used to improve the dispatching performance and provide insights into the corresponding scheduling problems. This paper uses timed Petri nets to describe the dispatching processes of the job shop scheduling scenarios. On this basis, a data mining based scheduling knowledge extraction framework is developed to mine the expected scheduling knowledge from the solutions generated by traditional optimization or approximation method for JSSP. Based on this, we show how to use the extracted knowledge as a new dispatching rule to generate complete schedules. A novel method is further developed to combine the extracted knowledge with traditional heuristics to construct new composite dispatching rules which could gain better performance. Besides, we propose a novel approach to utilize the extracted knowledge to improve a Petri net based branch and bound algorithm used in this paper. A series of experiments is carried out to evaluate the performance of the proposed methods. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Job shop scheduling Data mining Dispatching rule Petri net branch and bound algorithm

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Geospatial Ontology-based Mission Assignment in Wireless Sensor Networks

Geospatial Ontology-based Mission Assignment in Wireless Sen...

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2015 International Conference on Recent Advances in Internet of Things (RIoT)

作者： Ibrahim, Alia Carrez, Francois Moessner, Klaus Univ Surrey Inst Commun Syst Guildford Surrey England

ISBN: (纸本)9781479983254

Wireless Sensor Networks (WSNs) have been a focus for research in recent years. They enable data gathering across a wide range of domains and areas of interest from health service to environment monitoring, security, etc. Sensors are becoming cheaper, and as a result are being deployed in high density, at the same time;users' requirements of the network are changing frequently, they can even exceed the capabilities of the sensors in the network sometimes. The network is expected to operate for a long period of time with many nodes operating on batteries. These challenges have raised the attention to the problem of mission assignment in WSNs. Mission assignment aims at allocating tasks to specific sensors in the network -according to their capabilities-to answer users requirements while at the same time preserving the energy of the network. This paper approaches the problem of mission assignment from a geospatial perspective: because sensors' readings and data are associated with spatial properties of the sensors like their location and sensing range;spatial reasoning is an important aspect of mission assignment. However, spatial reasoning is still very limited in WSNs and has not received much attention because of the lack of standardized modelling of space. In the center of our approach an integration of two ontologies;the W3C semantic sensor network ontology (SSN) which describes sensor nodes in the network and GeoSPARQL (the OGC standard for modelling and reasoning about spatial data). We present Geospatial Sensor Mission Assignment algorithm (GeoSMA);a branch and bound algorithm based on the spatial functions and relations between tasks' and sensors' spatial properties. The aim is to find the most appropriate set of nodes to answer various missions required by the users.

关键词： branch and bound algorithm Geospatial analysis Ontology Wireless Sensor Networks, Mission assignment

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Improved Differential Characteristic Searching Methods 2

Improved Differential Characteristic Searching Methods

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2nd International Conference on Cyber Security and Cloud Computing (CS Cloud)

作者： Chen, Jiageng Miyaji, Atsuko Su, Chunhua Teh, Jesen Cent China Normal Univ Comp Sch Wuhan Peoples R China Japan Adv Inst Sci & Technol Sch Informat Sci Nomi Japan Japan Sci & Technol Agcy Kawaguchi Ctr Crest Kawaguchi Saitama Japan Osaka Univ Grad Sch Engn Suita Osaka 565 Japan Univ Sains Malaysia Informat Secur Lab George Town Malaysia

ISBN: (纸本)9781467393003

The success probability of differential and linear cryptanalysis against block ciphers heavily depend on finding differential or linear paths with high statistical bias compared with uniform random distribution. For large number of rounds, it is not a trivial task to find such differential or linear paths. Matsui first investigated this problem and proposed a solution based on a branch and bound algorithm in 1994. Since then, the research on finding good concrete differential or linear path did not receive much attention. In this paper, we revisit the differential attack against several S-Box based block ciphers by carefully studying the differential characteristics. Inspired by Matsui's algorithm, we provide an improved solution with the aid of several searching strategies, which enable us to find by far the best differential characteristics for the two investigated ciphers (LBlock, TWINE) efficiently. Furthermore, we provide another way to evaluate the security of ciphers against differential attack by comparing the strength of the ciphers from differential characteristic's point of view, and we also investigate the accuracy when using the active S-Box to evaluate the security margin against differential attack, which is the common method adapted when new ciphers are designed.

关键词： Differential Path branch and bound algorithm Active S-box LBlock TWINE

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School Bus Routing Based on branch and bound Approach

School Bus Routing Based on Branch and Bound Approach

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International Conference on Computer, Communication and Control

作者： Yash Kumar Sushma Jain Comput. Sci. & Eng. Dept. Thapar Univ. Patiala India

ISBN: (纸本)9781479981656

Congestion in the traffic is the most basic problem that most of the cities facing now a days. This problem is mainly evolved due to increase in travel demand and limited scope of increasing the infrastructure needed to hold that traffic. So from there comes the concept of vehicle routing problem and thus the problem of School Bus Routing Problem (SBRP). In the past Hungarian algorithm was used. Evolution of technology and day by day advancements in wireless communication and algorithms has lead us to use of branch and bound approach to solve this problem. In this paper, we explore efficient routing algorithm for SBRP. In, this paper, branch and bound Routing algorithm is proposed for SBRP. The branch and bound algorithm provide optimal solution for the smaller problems. For a group of schools it will provide an optimal solution that will help those schools to optimize the bus routes, number of buses used and thus optimizing cost. This will also help in reducing pollution as the distance travelled by buses is optimized.

关键词： Vehicle Routing Problem branch and bound algorithm School Bus Routing algorithm

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Improved Differential Characteristic Searching Methods

Improved Differential Characteristic Searching Methods

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IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)

作者： Jiageng Chen Atsuko Miyaji Chunhua Su Jesen Teh Computer School Central China Normal University Wuhan China Hokuriku Sentan Kagaku Gijutsu Daigakuin Daigaku Nomi Ishikawa JP School of Information Science Japan Advanced Institute of Science and Technology Nomi Japan Information Security Lab Universiti Sains Malaysia Malaysia

ISBN: (纸本)9781467393010

关键词： Differential Path branch and bound algorithm Active S-box LBlock TWINE differential attack Passwords branch and bound algorithms S-box Search methods round number Differential linear cryptanalysis Block cipher

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Constraint reformulation and a Lagrangian relaxation-based solution algorithm for a least expected time path problem

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2014年 59卷 22-44页

作者： Yang, Lixing Zhou, Xuesong Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Arizona State Univ Sch Sustainable Engn & Built Environm Tempe AZ 85287 USA

Using a sample-based representation scheme to capture spatial and temporal travel time correlations, this article constructs an integer programming model for finding the a priori least expected time paths. We explicitly consider the non-anticipativity constraint associated with the a priori path in a time-dependent and stochastic network, and propose a number of reformulations to establish linear inequalities that can be easily dualized by a Lagrangian relaxation solution approach. The relaxed model is further decomposed into two sub-problems, which can be solved directly by using a modified label-correcting algorithm and a simple single-value linear programming method. Several solution algorithms, including a sub-gradient method, a branch and bound method, and heuristics with additional constraints on Lagrangian multipliers, are proposed to improve solution quality and find approximate optimal solutions. The numerical experiments investigate the quality and computational efficiency of the proposed solution approach. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： A priori least expected time path Time-dependent traffic network Lagrangian relaxation branch and bound algorithm

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Non-Cyclic Scheduling of a Wet Station

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2014年第4期11卷 1262-1274页

作者： Kim, Hyun-Jung Lee, Jun-Ho Lee, Tae-Eog Korea Adv Inst Sci & Technol Dept Ind & Syst Engn Taejon 305701 South Korea

We examine a non-cyclic scheduling problem of a wet station that performs cleaning processes for removing residual contaminants on wafer surfaces. Several chemical and rinse baths, and multiple robots for transporting jobs are linearly combined in a wet station. A wet station in a fab tends to have different types of jobs. Therefore, it is realistic to consider non-cyclic release of jobs into a wet station. We therefore examine a non-cyclic scheduling problem of a wet station that determines the task sequence of each robot so as to minimize the makespan of a given sequence of different jobs. We develop an efficient branch and bound procedure by examining the scheduling problem. To do this, we first develop a Petri net model for the scheduling problem. By identifying deadlock prevention conditions from the Petri net model, we eliminate partial solutions in advance that eventually will lead to a deadlock. By examining the feasible transition firings or state transition behavior of the Petri net model, we branch only feasible partial solutions or nodes that correspond to feasible state transitions or transition firings. We also develop a tight lower bound based on the bottleneck workload of the baths. We prove computational efficiency of the branch and bound procedure for practical problems.

关键词： branch and bound algorithm cluster tool deadlock no-wait Petri nets wet station

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First order rejection tests for multiple-objective optimization

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JOURNAL OF GLOBAL OPTIMIZATION 2014年第4期58卷 653-672页

作者： Goldsztejn, Alexandre Domes, Ferenc Chevalier, Brice CNRS LINA UMR 6241 Nantes France Univ Nantes LINA UMR 6241 Nantes France Univ Nantes Nantes France

Three rejection tests for multi-objective optimization problems based on first order optimality conditions are proposed. These tests can certify that a box does not contain any local minimizer, and thus it can be excluded from the search process. They generalize previously proposed rejection tests in several regards: Their scope include inequality and equality constrained smooth or nonsmooth multiple objective problems. Reported experiments show that they allow quite efficiently removing the cluster effect in mono-objective and multi-objective problems, which is one of the key issues in continuous global deterministic optimization.

关键词： Multi-objective deterministic global optimization First order optimality conditions Interval analysis branch and bound algorithm Cluster effect

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A branch and bound algorithm for Extending the Lifetime of Wireless Sensor Networks

A Branch and Bound Algorithm for Extending the Lifetime of W...

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70th IEEE Vehicular Technology Conference

作者： Kim, Yong-hwan Lee, Heon-Jong Han, Youn-Hee Jeong, Young-Sik Korea Univ Technol & Educ Lab Intelligent Networks Cheonan South Korea Wonkwang Univ Grid Comp Lab Iksan South Korea

ISBN: (纸本)9781424425143

One of most critical issues in power-constrained wireless sensor networks is to maximize the network lifetime. Recently, studies have been made on scheduling sensor activity to prolong network lifetime. In this paper, we address the maximum set covers (MSC) problem to maximize the network lifetime and propose an energy-efficient sensor scheduling algorithm for the MSC problem based on the branch and bound approach. Simulation results show that the proposed algorithms can contribute to extending the network lifetime and its performance is better than the existing greedy-based algorithm.

关键词： branch and bound algorithm Wireless Sensor Network Network Lifetime Power Saving Sensor Scheduling

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