We introduce a meta-heuristic to combine simulated annealing with local search methods for CO problems. This new class of Markov chains leads to signiicantly more powerful optimization methods than either simulated annealing or local search. The main idea is to embed deterministic local search techniques into simulated annealing so that the chain explores only local optima. It makes large, glob...

In this paper we consider a repair shop location problem with uncertainties in demand. New local repair shops have to be opened at a number of locations. At these local repair shops, customers arrive with broken, but repairable, items. Customers go to the nearest open repair shop. Since they want to leave as soon as possible, a (small) inventory of working items is kept at the repair shops. A c...

Abstract. In this paper, the experiments with local search heuristic algorithms for the traveling salesman problem (TSP) are described. Since the ordinary local search heuristics very seldom yield solutions of high quality, we investigate the enhanced local search algorithms using the extended neighbourhood structures. We also examine the performance of the local search heuristics in an iterate...

This paper deals with the economic optimization of reinforced concrete box frames used in road construction. It shows the efficiency of four heuristic algorithms applied to a problem of 50 design variables. Heuristic methods used are the random walk and the descent local search. The metaheuristic methods are the threshold accepting and the simulated annealing. The four methods have been applied...

Different methods are available for simultaneous optimization of cross-section, topology and geometry of truss structures. Since the search space for this problem is very large, the probability of falling in local optimum is considerably high. On the other hand, different types of design variables (continuous and discrete) lead to some difficulties in the process of optimization. In this articl...

A new approach is proposed incorporating heuristic optimization algorithm with a switch to a local search algorithm for the multidisciplinary design of solid launch vehicle at conceptual level. Heuristic optimization algorithms such as Genetic Algorithm often may locate near optimum solutions at the expense of large function evaluations. Local search algorithms including both gradient and non g...

Local search is one of the fundamental paradigms for solving computationally hard combinatorial problems, including the constraint satisfaction problem (CSP). It provides the basis for some of the most successful and versatile methods for solving the large and difficult problem instances encountered in many real-life applications. Despite impressive advances in systematic, complete search algor...

Local search is an integral part of many meta-heuristic strategies that solve single objective optimisation problems. Essentially, the meta-heuristic is responsible for generating a good starting point from which a greedy local search will find the local optimum. Indeed, the best known solutions to many hard problems (such as the travelling salesman problem) have been generated in this hybrid w...