We present a new heuristic algorithm for graph bisection, based on an implicit notion of clustering. We describe how the heuristic can be combined with stochastic search procedures and a postprocess application of the Kernighan-Lin algorithm. In a series of time-equated comparisons with large-sample runs of pure Kernighan-Lin, the new algorithm demonstrates signiicant superiority in terms of th...

Local search with k-exchange neighborhoods, k-opt, is the most widely used heuristic method for the traveling salesman problem (TSP). This paper presents an effective implementation of k-opt in LKH-2, a variant of the Lin–Kernighan TSP heuristic. The effectiveness of the implementation is demonstrated with experiments on Euclidean instances ranging from 10,000 to 10,000,000 cities. The runtime ...

It is well known that many arc routing problems can be transformed into the Equality Generalized Traveling Salesman Problem (E-GTSP), which in turn can be transformed into a standard Asymmetric Traveling Salesman Problem (TSP). This opens up the possibility of solving arc routing problems using existing solvers for TSP. This paper evaluates the performance of the state-of-the art TSP solver Lin...

Different floating-point and fixed-point implementation issues of the Log-MAP algorithm for decoding turbo codes are studied. A theoretical framework is proposed to explain why the Log-MAP turbo decoders are more tolerant of overestimation of SNR than underestimation. A linear approximation (the Log-Lin algorithm) that allows for efficient ASIC implementations and results in negligble performan...

We present an extension to a hybrid graph-bisection algorithm developed by Bui et al. that uses vertex coalescing and the Kernighan-Lin variable-depth algorithm to minimize the size of the cut set. In the original heuris-tic technique, one iteration of vertex coalescing is used to improve the performance of the original Kernighan-Lin algorithm. We show that by performing vertex coalescing recur...

We address the Traveling Salesman Problem (TSP), a famous NP-hard combinatorial optimization problem. And we propose variable strategy reinforced approach, denoted as VSR-LKH, which combines three reinforcement learning methods (Q-learning, Sarsa and Monte Carlo) with well-known TSP algorithm, called Lin-Kernighan-Helsgaun (LKH). VSR-LKH replaces inflexible traversal operation in LKH, lets prog...

Recently, Lin and Rokne [10] introduced the so-called Taylor-Bernstein form as an inclusion function form for multidimensional functions. This form was theoretically shown to have the super-convergence property. Here, we present an improvement of Lin and Rokne’s Taylor-Bernstein form to make it more effective in practice. We test and compare the super-convergence behavior of the proposed form w...

Graphical Abstract “The most important factors in the choice of my current research topic were energy consumption and environmental pollution … The advice I wish had received is to be more patient …” Find out about Yuze Lin his Introducing Profile.

In this paper, we present an evolutionary algorithm application to partitioning VLSI circuits on subcircuits with minimal number of connections between them. The algorithm is characterized by a multi-layer chromosome structure. Due to this structure, the partition of circuits is possible without applying a repair mechanism in the algorithm. The test circuits chosen from literature and created r...

It is well recognized that collaborative learning enhances academic performance by pooling the diverse strengths of co-participants and by providing a healthy competitive learning environment. Existing techniques for forming collaborative groups emphasize on effective transfer of knowledge between learners. However, mastery of any subject requires not just knowledge, but a distinct set of learn...