Models and methods of solution of quadratic integer programming problems

Volkovich, O. V.; Roshchin, V. A.; Сергиенко, И. В.

doi:10.1007/bf01074820

Cited by 26 publications

(5 citation statements)

References 44 publications

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“…Therefore, ψ Ns DS ∈ {+1, −1} is used to denote the set of vectors. Motivated by [14], the quadratic integer programming is able to deal with the optimal value of the objective function (13), but there is an NP hard problem which was analyzed in [15]. For practical systems, it is time consuming to obtain an optimal solution.…”

Section: Ds Designmentioning

confidence: 99%

Ultra-wideband direct-sequence design approach for multiple narrowband interference suppression

Guo

Shi³

2013

J. of Syst. Eng. Electron.

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A novel direct sequence (DS) design method for suppressing the narrowband interference in DS spread spectrum ultra-wideband receivers is proposed. The method has low computational complexity and can be easily implemented in practical systems. Simulation results prove that the proposed method is effective to suppress the narrowband interference. Therefore, the integrity of both the ultra-wide bandwidth and the narrowband systems can be highly enhanced.Keywords: bit error rate (BER), narrowband interference, Rayleigh-Ritz, direct sequence (DS).

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Section: Ds Designmentioning

confidence: 99%

Ultra-wideband direct-sequence design approach for multiple narrowband interference suppression

Guo

Shi³

2013

J. of Syst. Eng. Electron.

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“…The optimization problem in ( 4) is a quadratic integer programming (QIP) [39]. As our aim is maintaining the best idle channel utilization efficiency at first, we analyze the problem in the following two cases.…”

Section: Problem Formulationmentioning

confidence: 99%

A Fair Multi-Channel Assignment Algorithm With Practical Implementation in Distributed Cognitive Radio Networks

Wei

2018

IEEE Access

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Designing an efficient spectrum assignment (SA) mechanism is a key issue for realizing dynamic spectrum access in cognitive radio network. In multi-channel selection based SA schemes, secondary users (SUs) are able to utilize multiple channels simultaneously to enhance the network throughput. However, a fairness problem may happen if few SUs utilize too many idle data channels that other SUs are left with no idle channels, thus increasing the blocking probability and reducing the fairness. Aiming at improving the network throughput with multi-channel selection capability while maintaining fairness among the SUs, in this paper, we propose a fair multi-channel assignment scheme (FMCA) for distributed cognitive radio networks. For the FMCA scheme, we design a new MAC framework for sensing and access contention resolution, which is integrated into the FMCA scheme. Channel-aggregation (CA) technique is used in each SU to enable the multi-channel selection ability. Considering both of the idle data channel utilization efficiency and the transmit power budget constrained CA ability of each SU, we analytically formulate a channel assignment problem according to the well-known Jain's fairness criterion. Our objective is to find a channel assignment with maximal fairness index for all SUs. The optimization problem is turned out to be a quadratic integer programming (QIP). According to the definition of Jain's fairness criterion, we design an algorithm to get the optimal solution of the QIP. With the optimal channel assignment solution, the FMCA scheme is realized in the channel assignment phase of the proposed MAC protocol. Extensive simulation results show that the proposed FMCA scheme gets a good tradeoff between throughput and fairness compared with the existing SA schemes. INDEX TERMSFair multi-channel assignment, channel-aggregation, cognitive radio, distributed cognitive radio networks, medium access control (MAC) protocol, fairness, throughput.

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“…Several methods exist for solution of the MIQP problem, however branch-and-bound method is superior to other methods such as decomposition method or logic-based method [3]. A review of different methods of solving MIQP problems can be found in [4]. Commercial optimization software (CPLEX, GUROBI) is able to solve the MIQP problems and there are also several toolboxes for MATLAB exist (OPTI Toolbox which uses SCIP solver [5], Hybrid toolbox [6]).…”

Section: Introductionmentioning

confidence: 99%

Implementation of Mixed-integer Programming on Embedded System

Novák

Chalupa

2015

Procedia Engineering

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One of the most widespread modern control strategies is the discrete-time Model Predictive Control (MPC) method which requires the solution of the quadratic programming problem. For systems with binary input variables the quadratic problem is replaced by more challenging Mixed-Integer Quadratic Programming (MIQP) problem. The objective of this work is the implementation of MIQP problem solver in a low power embedded computing platform with limited computational power and limited memory. The MIQP problem is solved using branch-and-bound method and the solution of the relaxed original quadratic problems with equality and inequality constraints solved in the nodes of a binary tree is found with interior-point algorithm. A simulation study of the reserve constrained economic dispatch problem for power generators with prohibited zones is presented. Simulation results show the applicability of the proposed solver for small size MIQP problems.

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Models and methods of solution of quadratic integer programming problems

Cited by 26 publications

References 44 publications

Ultra-wideband direct-sequence design approach for multiple narrowband interference suppression

Ultra-wideband direct-sequence design approach for multiple narrowband interference suppression

A Fair Multi-Channel Assignment Algorithm With Practical Implementation in Distributed Cognitive Radio Networks

Implementation of Mixed-integer Programming on Embedded System

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