In this paper, we study the over-constrained airport gate assignment problem where the objectives are to minimize the number of ungated 4ights and total walking distances or connection times. We 7rst use a greedy algorithm to minimize ungated 4ights. Exchange moves are employed to facilitate the use of heuristics. Simulated annealing and a hybrid of simulated annealing and tabu search are used....

In this paper we study a version of the Multidimensional Arrangement Problem (MAP) that embeds a graph into a multidimensional array minimizing the aggregated (Manhattan) distance of the embedded edges. This problem includes the minimum Linear Arrangement Problem (minLA) as a special case, among others. We propose JAM, a tabu-based two-stage simulated annealing heuristic for this problem. Our a...

We propose the use of metaheuristics for the resource-capacitated multilevel lot-sizing problem with general product structures, setup costs, setup times, and lead times. Initially, we develop a heuristic which moves production in time in order to obtain feasible solutions with good quality. Strategies for the short-term memory and long-term memory of tabu search are then included to guide the ...

Search heuristics, such as Tabu Search and Simulated Annealing, start from a single solution and incrementally change it in order to find better solutions. Given a particular problem, there are a large number of possible ways of formulating a search in order to solve it. The choice of search space, neighbourhood scheme, search heuristic and its many possible additions and enhancements are all e...

The multilevel thresholding problem is often treated as a problem of optimization of an objective function. This paper presents both adaptation and comparison of six meta-heuristic techniques to solve the multilevel thresholding problem: a genetic algorithm, particle swarm optimization, differential evolution, ant colony, simulated annealing and tabu search. Experiments results show that the ge...

We present a state-of-the-art survey of parallel meta-heuristic developments and results, discuss general design and implementation principles that apply to most meta-heuristic classes, instantiate these principles for the three meta-heuristic classes currently most extensively used—genetic methods, simulated annealing, and tabu search, and identify a number of trends and promising research dir...

This paper reports on our experiments with statistical search methods for solving lotsizing problems in production planning. In lotsizing problems the main objective is to generate a minimum cost production and inventory schedule, such that (i) customer demand is satisfied, and (ii) capacity restrictions imposed on production resources are not violated. We discuss our experiences in solving the...

Algorithms based on local search are popular for solving many optimization problems including the maximum satisfiability problem (MAXSAT). With regard to MAXSAT, the state of the art in performance for universal (i.e. non specialized solvers) seems to be variants of Simulated Annealing (SA) and MaxWalkSat (MWS), stochastic local search methods. Local search methods are conceptually simple, and ...

A cutting stock problem is one of the main and classical problems in operations research that is modeled as Lp < /div> problem. Because of its NP-hard nature, finding an optimal solution in reasonable time is extremely difficult and at least non-economical. In this paper, two meta-heuristic algorithms, namely simulated annealing (SA) and tabu search (TS), are proposed and deve...