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A DNA Computer Model to Solve integer programming problem

JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE 2011年第2期8卷 274-281页

作者： Gang, Fang Yan, Zhu Xian Univ Arts & Sci Dept Life Sci Xian 710065 Peoples R China Xian Univ Arts & Sci Dept Comp Sci Xian 710065 Peoples R China

A special DNA computer is designed to solve the integer programming problem. The main body of this kind of DNA computer is piezoelectric genosensor which combines the sensitivity of piezoelectric sensor and DNA hybridization reaction amplified by functionalized magnetic nano-microspheres. It has the merits of simple construction, label-free feature, time-saving detection speed, and conveniently available information. When used in DNA computing, compared with conventional DNA chip, its information is easier to process automatically. Thus it can be used conveniently to construct an automatic computing machine to solve more complicated problems in operational researches. Based on the piezoelectric genosensor and surface DNA computing theory, a new DNA computer model is proposed in this paper. It is suggested that the piezoelectric genosensor can be used as a potential DNA computing chip to construct an automatic DNA computer.

关键词： DNA Computer Functionalized Magnetic Nano-Microspheres integer programming problem Piezoelectric Genosensor

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An algorithm to solve multi-objective integer quadratic programming problem

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ANNALS OF OPERATIONS RESEARCH 2024年第1-3期332卷 433-459页

作者： Kushwah, Prerna Sharma, Vikas TIET Sch Math Patiala India

The multi-objective integer programming problem often occurs in multi-criteria decision making situations, where the decision variables are integers. In the present paper, we have discussed an algorithm for finding all efficient solutions of a multi-objective integer quadratic programming problem. The proposed algorithm is based on the aspect that efficient solutions of a multi-objective integer quadratic programming problem can be obtained by enumerating ranked solutions of an integer quadratic programming problem. For determining ranked solutions of an integer quadratic programming problem, we have constructed a related integer linear programming problem and from ranked solutions of this integer linear programming problem, ranked solutions of the original integer quadratic programming problem are generated. Theoretically, we have shown that the developed method generates the set of all efficient solutions in a finite number of steps, and numerically we have elaborated the working of our algorithm and compared our results with existing algorithms. Further, we have analyzed that the developed method is efficient for solving a multi-objective integer quadratic programming problem with a large number of constraints, variables and objectives.

关键词： Efficient set integer programming problem Multiple objective programming problem Quadratic programming problem

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On solving fuzzy rough multiobjective integer linear fractional programming problem

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019年第5期37卷 6499-6511页

作者： Ammar, El Saeed Eljerbi, Tarek Tanta Univ Fac Sci Dept Math Tanta Egypt

In solving real life fractional programming problem, we often face the state of uncertainty as well as hesitation due to various uncontrollable factors. To overcome these limitations, the fuzzy rough approach is applied to this problem. In this paper, an efficient method is proposed for solving fuzzy rough multiobjective integer linear fractional programming problem where all the variables and parameters are fuzzy rough numbers. Here, the fuzzy rough multiobjective problem transformed into an equivalent multiobjective integer linear fractional programming problem. Furthermore, from the obtained problem, five crisp multiobjective integer linear fractional programming problems are constructed and the resultant problems are solved as a crisp integer linear programming problem by using Dinkelbach concept. Finally, the effectiveness of the proposed procedure is illustrated through numerical examples.

关键词： Fractional programming integer programming problem triangular fuzzy rough numbers fuzzy rough linear programming

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Hybrid particle swarm optimization with chaotic search for solving integer and mixed integer programming problems

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Journal of Central South University 2014年第7期21卷 2731-2742页

作者：谭跃谭冠政邓曙光 School of Information Science and Engineering Central South University School of Communication and Electronic Engineering Hunan City University

A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization(PSO) with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming *** performances of CLSPSO are compared with those of other five hybrid algorithms combining PSO with chaotic search *** results indicate that in terms of robustness and final convergence speed,CLSPSO is better than other five algorithms in solving many of these ***,CLSPSO exhibits good performance in solving two high-dimensional problems,and it finds better solutions than the known ones.A performance index(PI) is introduced to fairly compare the above six algorithms,and the obtained values of(PI) in three cases demonstrate that CLSPSO is superior to all the other five algorithms under the same conditions.

关键词： particle swarm optimization chaotic search integer programming problem mixed integer programming problem

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Efficiency Improvement in Explicit Enumeration for integer programming problems

Efficiency Improvement in Explicit Enumeration for Integer P...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Chen, S. G. Tungnan Univ Dept Ind Management New Taipei Taiwan

ISBN: (纸本)9781479909865

An integer programming problem is a mathematical optimization or feasibility program in which some or all of the variables are restricted to be integers. In many cases, the problems can be divided into integer linear programming (ILP) problems and integer non-linear programming (INLP) problems. A more complex problems are mixed integer programming (MIP) problems. There are many algorithms to well solve ILP problems. However, there are relatively fewer algorithms to solve INLP problems. In most situations, the explicit enumeration method (EEM) can be used to solve both kinds of problems. EEM is very simple to implement but with the price of low efficiency. This paper proposes an efficient approach namely Chen's rearrangement to improve the efficiency in explicit enumeration for integer programming problems. Part of them can also be applied to MIP problems. An interesting example is explored to explain the proposed approach.

关键词： integer programming problem explicit enumeration exhausted search brute-force search

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Partitioning of Behavioral Descriptions with Exploiting Function-Level Parallelism

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2010年第2期E93A卷 488-499页

作者： Hara, Yuko Tomiyama, Hiroyuki Honda, Shinya Takada, Hiroaki Nagoya Univ Grad Sch Informat Sci Nagoya Aichi 4648603 Japan

A novel method to efficiently synthesize hardware from a large behavioral description in behavioral synthesis is proposed. For a program with functions executable in parallel, this proposed method determines a behavioral partitioning which simultaneously minimizes the overall datapath area and the complexity of the controller while maximizing performance of a synthesized circuit by fully exploiting function-level parallelism of a behavioral description. This method is formulated as an integer programming problem. Experimental results demonstrate that this method leads to a shift of the explorable design space so that superior solutions which could not be explored by earlier work are included, showing the effectiveness of our proposed method.

关键词： behavioral synthesis function-level partitioning integer programming problem

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An optimisation model and its effective beam search heuristics for floor-storage warehousing systems

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2010年第7期48卷 1947-1966页

作者： Nishi, T. Konishi, M. Osaka Univ Grad Sch Engn Sci Osaka 5608531 Japan Okayama Univ Grad Sch Nat Sci & Technol Okayama 7008530 Japan

This paper presents an optimisation model and its effective solution technique using beam search heuristic for floor-storage warehousing systems. For a floor-storage system, storage can be accessed from the top of stacks only. The objective is to minimise the number of re-handling operations by optimally determining the storage location and by grouping products for each customer that fit a given sequence for receiving and retrieving operations. An integer programming model is formulated and an approximate solution technique based on the beam search method is proposed to solve the problem by incorporating effective heuristics to reduce the search space using future receiving and retrieving requests. The effectiveness of the proposed method is demonstrated for industrial warehousing problems in a steel plant with 58 storage areas involving more than 3000 retrieving operations. The proposed solution method is shown to be more efficient than the traditional branch-and-bound method for solving integer programming problems.

关键词： warehousing floor-storage systems storage allocation beam search optimisation integer programming problem

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Function-level partitioning of sequential programs for efficient behavioral synthesis

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2007年第12期E90A卷 2853-2862页

作者： Hara, Yuko Tomiyama, Hiroyuki Honda, Shinya Takada, Hiroaki Ishii, Katsuya Nagoya Univ Grad Sch Informat Sci Dept Informat Engn Nagoya Aichi 4648603 Japan Nagoya Univ Ctr Informat Technol Nagoya Aichi 4648603 Japan

This paper proposes a behavioral level partitioning method for efficient behavioral synthesis from a large sequential program consisting of a set of functions. Our method optimally determines functions to be inlined into the main module and the other functions to be synthesized into sub modules in such a way that the overall datapath is minimized while the complexity of individual modules is lower than a certain level. The partitioning problem is formulated as an integer programming problem. Experimental results show the effectiveness of the proposed method.

关键词： behavioral synthesis function-level partitioning integer programming problem

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Energy-efficient hierarchical cooperative caching optimisation for 5G networks

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IET COMMUNICATIONS 2019年第6期13卷 687-695页

作者： Xie, Renchao Tang, Qinqin Huang, Tao Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China

The caching in fifth generation (5G) networks has been considered as a promising technique to reduce the duplicate traffic transmission and improve the users' quality of experience (QoE). Although many works have been done for caching in 5G networks, most of them focus on the content caching policy design to optimise the users' QoE, the issue to realise the energy efficiency of the whole network is not fully considered. Therefore, in this study, by introducing the hierarchical cooperative caching property, i.e. the core gateway and the base stations can cooperative cache the content, the authors study the problem of the hierarchical cooperative caching policy to realise the energy efficiency. They then formulate the hierarchical cooperative content placement problem as an integer programming problem to minimise the total energy consumption. Also, to reduce the computation complexity, the optimisation algorithm based on the idea of quantum-inspired evolutionary is proposed, which has the fast convergence and approximate to the optimal solution. Finally, extensive simulation results are illustrated to demonstrate the performance of the proposed scheme.

关键词： evolutionary computation cooperative communication cache storage integer programming 5G mobile communication telecommunication computing duplicate traffic transmission content caching policy design energy efficiency total energy consumption energy-efficient hierarchical 5G networks fifth-generation networks user QoE user quality-of-experience integer programming problem

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Prediction of RNA secondary structure with pseudoknots using integer programming

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BMC BIOINFORMATICS 2009年第Sup1期10卷 1-11页

作者： Poolsap, Unyanee Kato, Yuki Akutsu, Tatsuya Kyoto Univ Inst Chem Res Bioinformat Ctr Kyoto 6110011 Japan

Background: RNA secondary structure prediction is one major task in bioinformatics, and various computational methods have been proposed so far. Pseudoknot is one of the typical substructures appearing in several RNAs, and plays an important role in some biological processes. Prediction of RNA secondary structure with pseudoknots is still challenging since the problem is NP-hard when arbitrary pseudoknots are taken into consideration. Results: We introduce a new method of predicting RNA secondary structure with pseudoknots based on integer programming. In our formulation, we aim at minimizing the value of the objective function that reflects free energy of a folding structure of an input RNA sequence. We focus on a practical class of pseudoknots by setting constraints appropriately. Experimental results for a set of real RNA sequences show that our proposed method outperforms several existing methods in sensitivity. Furthermore, for a set of sequences of small length, our approach achieved good performance in both sensitivity and specificity. Conclusion: Our integer programming-based approach for RNA structure prediction is flexible and extensible.

关键词： integer programming integer programming problem integer programming Formulation Pseudoknotted Structure Grammatical Approach

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