This paper presents a non-crossover and multi-mutation based genetic algorithm (NMGA) for the Flexible Job-shop Scheduling problem (FJSP) with the criterion to minimize the maximum completion time (makespan). Aiming at the characteristics of FJSP, three mutation operators based on operation sequence coding and machine assignment coding are proposed: flip, slide, and swap. Meanwhile, the NMGA framework, coding scheme, as well as the decoding algorithm are also specially designed for the FJSP. In the framework, recombination operator crossover is not included and a special selection strategy is employed. Computational results based on a set of representative benchmark problems were provided. The evidence indicates that the proposed algorithm is superior to several recently published genetic algorithms in terms of solution quality and convergence ability.

A hinge vertex is a vertex in an undirected graph such that there exist two vertices whose removal makes the distance between them longer than before. Identifying hinge vertices in a graph can help detect critical nodes in communication network systems, which is useful for making them more stable. For finding them, an O(n3) time algorithm was developed for a simple graph, and, linear time algorithms were developed for interval and permutation graphs, respectively. Recently, the maximum detour hinge vertex problem is defined by Honma et al. For a hinge vertex u in a graph, the detour degree of u is the largest value of distance between any pair of x and y (x and y are adjacent to u) by removing u. A hinge vertex with the largest detour degree in G is defined as the maximum detour hinge vertex of G. This problem is motivated by practical applications, such as network stabilization with a limited cost, i.e., by enhancing the reliability of the maximum detour hinge vertex, the stability of the network is much improved. We previously developed an O(n2) time algorithm for solving this problem on an interval graph. In this study, we propose an algorithm that identifies the maximum detour hinge vertex on a permutation graph in O(n2) time, where n is the number of vertices in the graph.

In this paper, we propose a zero-forcing (ZF) Tomlinson-Harashima precoding (THP) with substream permutations based on the bit rate maximization for single-user MIMO (SU-MIMO) systems. We study the effect of substream permutations on the ZF-THP SU-MIMO systems, when the mean squared error (MSE) and the bit rate are adopted for the selection of the permutation matrix as criteria. Based on our analysis, we propose a method to increase the bit rate by substream permutations, and derive QR and Cholesky decomposition-based algorithms which realize the proposed method. Furthermore, to improve the error rate performance, we apply zero transmission to subchannels with low signal-to-noise ratios. Numerical examples are provided to demonstrate the effectiveness of the proposed THP MIMO system.

Ordered Binary Decision Diagrams (OBDDs for short) are popular dynamic data structures for Boolean functions. In some modern applications, we have to handle such huge graphs that the usual explicit representations by adjacency lists or adjacency matrices are infeasible. To deal with such huge graphs, OBDD-based graph representations and algorithms have been investigated. Although the size of OBDD representations may be large in general, it is known to be small for some special classes of graphs. In this paper, we show upper bounds and lower bounds of the size of OBDDs representing some intersection graphs such as bipartite permutation graphs, biconvex graphs, convex graphs, (2-directional) orthogonal ray graphs, and permutation graphs.

Multi-antenna relay transport protocols are analysed, the transmitting matrix of relay node can split into a forward and a backward filters, and these two filters are cascade connection. Based on the zero-forcing relaying protocol, a spatial channel mapping matrix is added between these two filters, and a unified framework of spatial channel mapping matrix is proposed. Then, various linear system designs are summarized, the spatial channel mapping matrix is used to reduce destination noise, so that the relaying noise is suppressed in destination node, and the transmitting power of relay is efficiently utilized. Meanwhile, source node preprocessing operation and destination node equalizer are considered. Simulation results show that the spatial channel mapping matrix has an advantage in terms of system outage probability and capacity performance, and the result is consistent with theoretical analysis.

We aim at constructing adaptive oblivious transfer protocols, enjoying fully simulatable security, from various well-known assumptions such as DDH, d-Linear, QR, and DCR. To this end, we present two generic constructions of adaptive OT, one of which utilizes verifiable shuffles together with threshold decryption schemes, while the other uses permutation networks together with what we call loosely-homomorphic key encapsulation schemes. The constructions follow a novel designing approach called “blind permutation”, which completely differs from existing ones. We then show that specific choices of the building blocks lead to concrete adaptive OT protocols with fully simulatable security in the standard model under the targeted assumptions. Our generic methods can be extended to build universally composable (UC) secure OT protocols, with a loss in efficiency.

The emergence of nature-inspired algorithms (NIA) is a great milestone in the field of computational intelligence community. As one of the NIAs, the artificial immune algorithm (AIS) mimics the principles of the biological immune system, and has exhibited its effectiveness, implicit parallelism, flexibility and applicability when solving various engineering problems. Nevertheless, AIS still suffers from the issues of evolution premature, local minima trapping and slow convergence due to its inherent stochastic search dynamics. Much effort has been made to improve the search performance of AIS from different aspects, such as population diversity maintenance, adaptive parameter control, etc. In this paper, we propose a novel multi-learning operator into the AIS to further enrich the search dynamics of the algorithm. A framework of embedding multiple commonly used mutation operators into the antibody evolution procedure is also established. Four distinct learning operators including baldwinian learning, cauchy mutation, gaussian mutation and lateral mutation are selected to merge together as a multi-learning operator. It can be expected that the multi-learning operator can effectively balance the exploration and exploitation of the search by enriched dynamics. To verify its performance, the proposed algorithm, which is called multi-learning immune algorithm (MLIA), is applied on a number of benchmark functions. Experimental results demonstrate the superiority of the proposed algorithm in terms of convergence speed and solution quality.

This paper presents an efficient method for differential fault analysis (DFA) on substitution-permutation network (SPN)-based block ciphers. A combination of a permutation cancellation and an algebraic key filtering technique makes it possible to reduce the computational cost of key filtering significantly and therefore perform DFAs with new fault models injected at an earlier round, which defeats conventional countermeasures duplicating or recalculating the rounds of interest. In this paper, we apply the proposed DFA to the LED block cipher. Whereas existing DFAs employ fault models injected at the 30th round, the proposed DFA first employs a fault model injected at the 29th round. We demonstrate that the proposed DFA can obtain the key candidates with only one pair of correct and faulty ciphertexts in about 2.1h even from the 29th round fault model and the resulting key space is reduced to 24.04

The Hierarchical Memory Machine (HMM) is a theoretical parallel computing model that captures the essence of computation on CUDA-enabled GPUs. The offline permutation is a task to copy numbers stored in an array a of size n to an array b of the same size along a permutation P given in advance. A conventional algorithm can complete the offline permutation by executing b[p[i]] ← a[i] for all i in parallel, where an array p stores the permutation P. We first present that the conventional algorithm runs $D_w(P)+2{nover w}+3L-3$ time units using n threads on the HMM with width w and latency L, where Dw(P) is the distribution of P. We next show that important regular permutations including transpose, shuffle, and bit-reversal permutations run $2{nover w}+2{nover kw}+2L-2$ time units on the HMM with k DMMs. We have implemented permutation algorithms for these regular permutations on GeForce GTX 680 GPU. The experimental results show that these algorithms run much faster than the conventional algorithm. We also present an offline permutation algorithm for any permutation running in $16{nover w}+16{nover kw}+16L-16$ time units on the HMM with k DMMs. Quite surprisingly, our offline permutation algorithm on the GPU achieves better performance than the conventional algorithm in random permutation, although the running time has a large constant factor. We can say that the experimental results provide a good example of GPU computation showing that a complicated but ingenious implementation with a larger constant factor in computing time can outperform a much simpler conventional algorithm.

The relay channel is the common approach to cooperative communication. Quasi-cyclic low-density parity-check (QC-LDPC) code design for the relay channel is important to cooperative communication. This paper proposes a bilayer QC-LDPC code design scheme for the relay channel. Combined with the bilayer graphical code structure, an improved Chinese remainder theorem (CRT) method, the Biff-CRT method is presented. For the proposed method we introduce a finite field approach. The good performance of the finite field based QC-LDPC code can improve the performance of its corresponding objective QC-LDPC code in the proposed scheme. We construct the FF code and the FA code by the Biff-CRT method. The FF code and the FA code are both named as their two component codes. For the FF code, the two component code are both finite field based QC-LDPC codes. For the FA code, one of the component codes is the finite field based QC-LDPC code and the other is the array code. For the existing CRT method, the shortened array code and the array code are usually used as the component codes to construct the SA code. The exponent matrices of FF code, FA code and SA code are given both for the overall graph and the lower graph. Bit error rate (BER) simulation results indicate that the proposed FF code and FA code are superior to the SA code both at the relay node and the destination node. In addition, the theoretical limit and the BER of the bilayer irregular LDPC code are also given to compare with the BER of the proposed QC-LDPC codes. Moreover, the proposed Biff-CRT method is flexible, easy to implement and effective for constructing the QC-LDPC codes for the relay channel, and it is attractive for being used in the future cooperative communication systems.

Pattern-avoiding permutations are permutations where none of the subsequences matches the relative order of a given pattern. Pattern-avoiding permutations are related to practical and abstract mathematical problems and can provide simple representations for such problems. For example, some floorplans, which are used for optimizing very-large-scale integration (VLSI) circuit design, can be encoded into pattern-avoiding permutations. The generation of pattern-avoiding permutations is an important topic in efficient VLSI design and mathematical analysis of patten-avoiding permutations. In this paper, we present an algorithm for generating pattern-avoiding permutations, and extend this algorithm beyond classical patterns to generalized patterns with more restrictions. Our approach is based on the data structure πDDs, which can represent a permutation set compactly and has useful set operations. We demonstrate the efficiency of our algorithm by computational experiments.

The Generalized Feistel Structure (GFS) is one of the structures used in designs of blockciphers and hash functions. There are several types of GFSs, and we focus on Type 1 and Type 2 GFSs. The security of these structures are well studied and they are adopted in various practical blockciphers and hash functions. The round function used in GFSs consists of two layers. The first layer uses the nonlinear function. Type 1 GFS uses one nonlinear function in this layer, while Type 2 GFS uses a half of the number of sub-blocks. The second layer is a sub-block-wise permutation, and the cyclic shift is generally used in this layer. In this paper, we formalize Type 1.x GFS, which is the natural extension of Type 1 and Type 2 GFSs with respect to the number of nonlinear functions in one round. Next, for Type 1.x GFS using two nonlinear functions in one round, we propose a permutation which has a good diffusion property. We demonstrate that Type 1.x GFS with this permutation has a better diffusion property than other Type 1.x GFS with the sub-block-wise cyclic shift. We also present experimental results of evaluating the diffusion property and the security against the saturation attack, impossible differential attack, differential attack, and linear attack of Type 1.x GFSs with various permutations.

In this paper, we apply a mutation operation based on a multivariate Cauchy distribution to fast evolutionary programming and analyze its effect in terms of various function optimizations. The conventional fast evolutionary programming in-cooperates the univariate Cauchy mutation in order to overcome the slow convergence rate of the canonical Gaussian mutation. For a mutation of n variables, while the conventional method utilizes n independent random variables from a univariate Cauchy distribution, the proposed method adopts n mutually dependent random variables that satisfy a multivariate Cauchy distribution. The multivariate Cauchy distribution naturally has higher probabilities of generating random variables in inter-variable regions than the univariate Cauchy distribution due to the mutual dependence among variables. This implies that the multivariate Cauchy random variable enhances the search capability especially for a large number of correlated variables, and, as a result, is more appropriate for optimization schemes characterized by interdependence among variables. In this sense, the proposed mutation possesses the advantage of both the univariate Cauchy and Gaussian mutations. The proposed mutation is tested against various types of real-valued function optimizations. We empirically find that the proposed mutation outperformed the conventional Cauchy and Gaussian mutations in the optimization of functions having correlations among variables, whereas the conventional mutations showed better performance in functions of uncorrelated variables.

We consider the minimum feedback vertex set problem for some bipartite graphs and degree-constrained graphs. We show that the problem is linear time solvable for bipartite permutation graphs and NP-hard for grid intersection graphs. We also show that the problem is solvable in O(n2log 6n) time for n-vertex graphs with maximum degree at most three.

This paper deals with the problem of underdetermined blind source separation (BSS) where the number of sources is unknown. We propose a BSS approach that simultaneously estimates the number of sources, separates the sources based on the sparseness of speech, estimates the direction of arrival of each source, and performs permutation alignment. We confirmed experimentally that reasonably good separation was obtained with the present method without specifying the number of sources.

Let Gs=(Vs, Es) be a simple connected graph. A vertex v ∈ Vs is an articulation vertex if deletion of v and its incident edges from Gs disconnects the graph into at least two connected components. Finding all articulation vertices of a given graph is called the articulation vertex problem. A vertex u ∈ Vs is called a hinge vertex if there exist any two vertices x and y in Gs whose distance increase when u is removed. Finding all hinge vertices of a given graph is called the hinge vertex problem. These problems can be applied to improve the stability and robustness of communication network systems. In this paper, we propose linear time algorithms for the articulation vertex problem and the hinge vertex problem of circular permutation graphs.

PREIMAGE CONSTRUCTION problem by Kratsch and Hemaspaandra naturally arose from the famous graph reconstruction conjecture. It deals with the algorithmic aspects of the conjecture. We present an O(n8) time algorithm for PREIMAGE CONSTRUCTION on permutation graphs and an O(n4(n+m)) time algorithm for PREIMAGE CONSTRUCTION on distance-hereditary graphs, where n is the number of graphs in the input, and m is the number of edges in a preimage. Since each graph of the input has n-1 vertices and O(n2) edges, the input size is O(n3) (, or O(nm)). There are polynomial time isomorphism algorithms for permutation graphs and distance-hereditary graphs. However the number of permutation (distance-hereditary) graphs obtained by adding a vertex to a permutation (distance-hereditary) graph is generally exponentially large. Thus exhaustive checking of these graphs does not achieve any polynomial time algorithm. Therefore reducing the number of preimage candidates is the key point.

In this paper, we study a boomerang attack approach on MD4-based hash functions, and present a practical 4-sum distinguisher against the compression function of the full 5-pass HAVAL. Our approach is based on the previous work by Kim et al., which proposed the boomerang distinguisher on the encryption mode of MD4, MD5, and HAVAL in the related-key setting. Firstly, we prove that the differential path for 5-pass HAVAL used in the previous boomerang distinguisher contains a critical flaw and thus the attack cannot work. We then search for new differential paths. Finally, by using the new paths, we mount the distinguisher on the compression function of the full 5-pass HAVAL which generates a 4-sum quartet with a complexity of approximately 211 compression function computations. As far as we know, this is the first result on the full compression function of 5-pass HAVAL that can be computed in practice. We also point out that the 4-sum distinguisher can also be constructed for other MD4-based hash functions such as MD5, 3-pass HAVAL, and 4-pass HAVAL. Our attacks are implemented on a PC and we present a generated 4-sum quartet for each attack target.

The Generalized Feistel Structure (GFS) generally uses the sub-block-wise cyclic shift in the permutation layer, the layer between the two F function layers. For Type 2 GFS, at FSE 2010, Suzaki and Minematsu showed that a better diffusion property can be obtained if one uses some other sub-block-wise permutation. In this paper, we consider Type 1, Type 3, Source-Heavy (SH), and Target-Heavy (TH) GFSs, and study if their diffusion properties can be improved by changing the sub-block-wise cyclic shift. For Type 1 GFS and Type 3 GFS, we show that better permutations in terms of diffusion exist. For SH and TH GFSs, we show that the diffusion property does not change even if we change the sub-block-wise cyclic shift. We also experimentally derive optimum permutations in terms of diffusion, and evaluate the security of the resulting schemes against saturation, impossible differential, differential, and linear attacks.

Permutation polynomial based interleavers over integer rings, in particular quadratic permutation polynomials have been widely studied. In this letter, higher degree permutation polynomials for interleavers are considered for interleavers and permutation polynomials superior to quadratic permutation polynomials are found for some lengths.