We consider a new class of optimization heuristics which combine local searches with stochastic sampling methods, allowing one to iterate local optimization heuristics. We have tested this on the Euclidean Traveling Salesman Problem, improving 3-opt by over 1.6% and Lin-Kernighan by 1.3%.

In this paper we present effective new local and variable neighbourhood search heuristics for the asymmetric Travelling Salesman Problem. Our local search approach, HyperOpt, is inspired by a heuristic developed for a sequencing problem arising in the manufacture of printed circuit boards. In our approach we embed an exact algorithm into a local search heuristic in order to exhaustively search ...

A new genetic algorithm for the solution of the travelling salesman problem is presented in this paper. The approach is to introduce several knowledge-augmented genetic operators which guide the genetic algorithm more directly towards better quality of the populationbut are not trapped in local optima prematurely. The algorithm applies a greedy crossover and two advanced mutation operations bas...

This work presents a hybrid method for motif discovery in DNA sequences. The proposed method called SPSO-Lk, borrows the concept of Chebyshev polynomials and uses the stochastic local search to improve the performance of the basic PSO algorithm as a motif finder. The Chebyshev polynomial concept encourages us to use a linear combination of previously discovered velocities beyond that proposed b...

This paper introduces the optimization algorithm to improve search rate in urban path routing problems using viral infection and local search in urban environment. This algorithm operates based on two different approaches including wavelet transform and genetic algorithm. The variables proposed by driver such as degree of difficulty and difficulty traffic are of the essence in this technique. W...

The rational flight landing sequence has very important influence on the service of airlines, airports and air traffic controller. The discrete optimization problem can be seen as one machine scheduling problem with distinct starting and finishing time and the objective: the minimization of tardy flight problem. Because of this NP-hard complexity, ant colony optimization (ACO) is utilized to so...

This paper presents an improved chaotic ant colony system algorithm (ICACS) for solving combinatorial optimization problems. The existing algorithms still have some imperfections, we use a combination of two different operators to improve the performance of algorithm in this work. First, 3-opt local search is used as a framework for the implementation of the ACS to improve the solution quality;...

The probabilistic traveling salesman problem concerns the best way to visit a set of customers located in some metric space, where each customer requires a visit only with some known probability. A solution to this problem is an a priori tour which visits all customers, and the objective is to minimize the expected length of the a priori tour over all customer subsets, assuming that customers i...

With the rapid development of modern logistics industry, multi-compartment vehicle routing problem (MCVRP) is one of the research directions of vehicle routing problem, mainly to solve the problem of the transportation of non-mixed products in one vehicle. These products must be stored in separate compartments, and should not exceed the capacity of the carriage. A hybrid fruit fly optimization ...