Exponential chaotic tabu search hardware for quadratic assignment problems using switched-current chaotic neuron IC

Matsui, Shouichi; Kobayashi, Yuuta; Watanabe, Kenta; Horio, Yoshihiko

doi:10.1109/ijcnn.2004.1380965

Cited by 5 publications

(8 citation statements)

References 6 publications

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“…Furthermore, Table 1 confirms the relationship (19), and that the convex relaxation approach gives the best lower bound.…”

Section: Quality Of the Relaxationssupporting

confidence: 67%

“…So summarizing, for the numerical example considered here the ranking (19) of these bounds reads: EVB % 0:023 6 PEVB % 0:181 6 QPB % 0:215…”

Section: Quadratic Programming Boundmentioning

confidence: 97%

“…In [18] the authors present a ant colony optimization method that is combined with a local search algorithm. The authors in [19] proposed a chaos driven tabu search neural network hardware system to solve the QAP.…”

Section: Related Workmentioning

confidence: 99%

“…The quality of the various relaxation approaches, namely the eigenvalue bound (EVB), the projected eigenvalue bound (PEVB) and the quadratic programming bound (QPB), can be assessed by measuring how close these bounds are to the global optimum (see (19)). Table 1 shows the results for problems drawn from the QAPLIB [45].…”

Section: Quality Of the Relaxationsmentioning

confidence: 99%

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Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views

Schellewald

Roth

Schnörr

2007

Image and Vision Computing

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“…Furthermore, Table 1 confirms the relationship (19), and that the convex relaxation approach gives the best lower bound.…”

Section: Quality Of the Relaxationssupporting

confidence: 67%

“…So summarizing, for the numerical example considered here the ranking (19) of these bounds reads: EVB % 0:023 6 PEVB % 0:181 6 QPB % 0:215…”

Section: Quadratic Programming Boundmentioning

confidence: 97%

Section: Related Workmentioning

confidence: 99%

Section: Quality Of the Relaxationsmentioning

confidence: 99%

See 2 more Smart Citations

Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views

Schellewald

Roth

Schnörr

2007

Image and Vision Computing

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“…We have also conducted a course of research on hybrid computational systems, which fuse highly parallel analog real-number computations based on high-dimensional physical chaotic dynamics with serial digital computation based on algorithms; this was inspired by the computational style of the brain, which uses mutual interactions between conscious and sub-conscious processes [6][7][8][9]. Examples of our hardware systems are the chaotic tabu search system for quadratic assignment problems (QAPs), and the general-purpose chaotic neuro-computer system [6][7][8][9][10]. These hybrid computational hardware systems share the properties of large-scale complex systems mentioned above.…”

Section: Introductionmentioning

confidence: 99%

Partial-update exponential chaotic tabu search for a large-scale analog/digital hybrid electronic system

Horio

Ozawa

Miura

2015

NOLTA

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A salient feature of complex systems is their inherent robustness against poor and fluctuating characteristics of constituent elements, systematic offsets in parameter values, environmental changes, noise, and other such fluctuations. In spite of such unreliable, poorquality, and highly variable elements, complex systems generally exhibit high-quality behavior as a whole. In this paper, we exploit this inherent robustness of complex systems to create a compact and efficient realization of a hardware system for exponential chaotic tabu search. We start from a synchronous exponential chaotic tabu search algorithm and develop a novel partial-update exponential chaotic tabu search algorithm. The proposed algorithm is suitable for a large-scale analog/digital hybrid hardware implementation. In addition, a hardware system architecture suitable for the partial-update exponential chaotic tabu search is proposed, and a switched-current chaotic neuron integrated circuit dedicated to the proposed system architecture is also designed. We investigate the feasibility of implementing the digital part of the system with a field-programmable gate array.Key Words: complex systems, analog/digital hybrid hardware, quadratic assignment problems, chaotic tabu search, chaotic neuron, nonlinear analog integrated circuits Partial-update exponential chaotic tabu searchThe following summarizes the modified SECT-MA-woW/Eta discussed above, which we refer to as the "partial-update exponential chaotic tabu" (PUECT) search. PUECT:PU-1 We quasi-randomize matrices A and B by applying row and column substitution matrices to them several times. PU-2We use U = 5, and set AF R ≈ 10-15% by tuning the value of θ ζ . PU-3A group of 50 neurons is updated simultaneously. PU-4We select the first 5 fired neurons in ascending order of neuron index. PU-5The current permutation p current is updated with the selected 5 neurons resulting in 5 different permutations: p 1 , p 2 , . . . , p 5 . PU-6We select the permutation p M from the resulting 5 permutations that gives the largest value of ΔF p M (t). If ΔF p M (t) > 0, then p current is replaced with p M . Otherwise, we keep p current .

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A variable neighbourhood search enhanced estimation of distribution algorithm for quadratic assignment problems

2020

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Quadratic Assignment Problem (QAP) is one of the most complex combinatorial optimization problems. Many real-world problems such as printed circuit board design, facility location problems, assigning gates to airplanes can be modelled as QAP. Problems of size greater than 35 is not able to solve optimally using conventional optimization methods. This warrants the use of evolutionary optimization methods for obtaining optimal or near optimal solutions for QAPs. This work proposes a hybridization on a univariate Estimation of Distribution Algorithm, namely the Population Based Incremental Learning Algorithm (PBILA), with Variable Neighbourhood Search (VNS) for solving QAPs. The proposed algorithm is employed to solve benchmark instances of QAP and the results are reported. The results of this work reveals that PBILA on its own is not efficient for solving the QAPs. However, when hybridised with VNS, the algorithm performs well providing best known solutions for 95 test instances out of the 101 instances considered. For most of the test instances, the percentage deviation is less than one percentage. The overall average percentage deviation of the obtained solutions from the best-known solutions is 0.037%, which is a significant improvement when compared with stateof-the-art algorithms.

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Exponential chaotic tabu search hardware for quadratic assignment problems using switched-current chaotic neuron IC

Cited by 5 publications

References 6 publications

Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views

Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views

Partial-update exponential chaotic tabu search for a large-scale analog/digital hybrid electronic system

A variable neighbourhood search enhanced estimation of distribution algorithm for quadratic assignment problems

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