Different initial solution generators in genetic algorithms for solving the probabilistic traveling salesman problem

The probabilistic traveling salesman problem (PTSP) is a topic of theoretical and practical importance in the study of stochastic network problems. It provides researchers with a modeling framework for exploring the stochastic effects in routing problems. This paper proposed three initial solution generators (NN1, NN2, RAN) under a genetic algorithm (GA) framework for solving the PTSP. A set of numerical experiments based on heterogeneous and homogeneous PTSP instances were conducted to test the effectiveness and efficiency of the proposed algorithms. The results from the heterogeneous PTSP show that the average E[τ] values obtained by the three generators under a GA framework are similar to those obtained by the “Previous Best,” but with an average computation time saving of 50.2%. As for the homogeneous PTSP instances, NN1 is a relatively better generator among the three examined, while RAN consistently performs worse than the other two generators in terms of average E[τ] values. Additionally, as compared to previously reported studies, no one single algorithm consistently outperformed the others across all homogeneous PTSP instances in terms of the best E[τ] values. The fact that no one initial solution generator consistently performs best in terms of the E[τ] value obtained across all instances in heterogeneous cases, and that the performance of each examined algorithm is dependent on the number of nodes (n) and probability (p) for homogeneous cases, suggest the possibility of context-dependent phenomenon. Finally, to obtain valid results, researchers are advised to include at least a certain amount of test instances with the same combination of n and p when conducting PTSP experiments.     

Antiblocking decoding

Based on the notion of an antiblocking system a new decoding algorithm is developed which is comparable with the permutation decoding algorithm, but more efficient.     

The pinnacle set of a permutation

The peak set of a permutation records the indices of its peaks. These sets have been studied in a variety of contexts, including recent work by Billey, Burdzy, and Sagan, which enumerated permutations with prescribed peak sets. In this article, we look at a natural analogue of the peak set of a permutation, instead recording the values of the peaks. We define the “pinnacle set” of a permutation $w$ to be the set $\{w\left(i\right):i\text{ is a peak of}w\}$. Although peak sets and pinnacle sets mark the same phenomenon for a given permutation, the behaviors of these sets differ in notable ways as distributions over the symmetric group. In the work below, we characterize admissible pinnacle sets and study various enumerative questions related to these objects.     

The compositional inverse of a class of bilinear permutation polynomials over finite fields of characteristic 2

Laigle-Chapuy constructed a class of permutation polynomials over a finite field of characteristic 2, which includes several other known classes. In this paper, we determine the compositional inverses of all Laigle-Chapuy's permutation polynomials. Our method is based on a direct sum decomposition of the finite field.     

A note on APN permutations in even dimension

APN permutations in even dimension are vectorial Boolean functions that play a special role in the design of block ciphers. We study their properties, providing some general results and some applications to the low-dimension cases. In particular, we prove that none of their components can be quadratic. For an APN vectorial Boolean function (in even dimension) with all cubic components we prove the existence of a component having a large number of balanced derivatives. Using these restrictions, we obtain the first theoretical proof of the non-existence of APN permutations in dimension 4. Moreover, we derive some constraints on APN permutations in dimension 6.     

On permutation representations of polyhedral groups

We answer affirmatively the following question of Derek Holt: Given integers , can one, in a simple manner, find a finite set and permutations such that has order , has order and has order ? The method of proof enables us to prove more general results (Theorems 2 and 3).

     

On the boomerang uniformity of permutations of low Carlitz rank

Finding permutation polynomials with low differential and boomerang uniformity is an important topic in S-box designs of many block ciphers. For example, AES chooses the inverse function as its S-box, which is differentially 4-uniform and boomerang 6-uniform. Also there has been considerable research on many non-quadratic permutations which are modifications of the inverse function. In this paper, we give a novel approach which shows that plenty of existing modifications of the inverse function are in fact affine equivalent to permutations of low Carlitz rank, and those modifications cannot be APN. We also present the complete list of permutations of Carlitz rank 3 having the boomerang uniformity six, and give the complete classification of the differential uniformities of permutations of Carlitz rank 3. As an application, we provide all the involutions of Carlitz rank 3 having the boomerang uniformity six.     

Survivability strategies with backup multiplexing in WDM optical networks

In this paper, we have presented four variations of applying the same routing algorithm for primary and backup lightpaths, wavelength assignment strategy for survivability. The simulation results show that although everything is the same, yet how and when they are applied leads to variations in results in terms of number of connections accepted. The backup multiplexing technique has been incorporated to reduce the blocking probability in all the strategies. The results have been calculated both for the systems that require 100% degree of survivability, i.e. critical, and for those that do not. The variation to be used depends upon whether the application is critical or not.     

Nonlinear bipartite matching

We study the problem of optimizing nonlinear objective functions over bipartite matchings. While the problem is generally intractable, we provide several efficient algorithms for it, including a deterministic algorithm for maximizing convex objectives, approximative algorithms for norm minimization and maximization, and a randomized algorithm for optimizing arbitrary objectives.