Rotating workforce scheduling is a typical constraint satisfaction problem which appears in a broad range of work places (e.g. industrial plants). Solving this problem is of a high practical relevance. In this paper we propose the combination of tabu search with random walk and min conflicts strategy to solve this problem. Computational results for benchmark examples in literature and other rea...

Simulated annealing is a powerful stochastic search method, but it still has the disadvantage of blind search. Tabu search (TS) which can prevent cycling and enhance diversi/cation, is an adaptive strategy based on tabu list. By reasonably combining simulated annealing with TS, an e#ective hybrid algorithm for the problem of packing circles into a larger containing circle is presented. Based on...

This paper addresses the problem of scheduling ambulance crews in order to maximize the coverage throughout a planning horizon. The problem includes the subproblem of locating ambulances to maximize expected coverage with probabilistic response times, for which a tabu search algorithm is developed. The proposed tabu search algorithm is empirically shown to outperform previous approaches for thi...

In this paper we propose a new tabu search hyperheuristic which makes individual low level heuristics tabu dynamically using an analogy with the Binary Exponential Back Off (BEBO) method used in network communication. We compare this method to a reduced Variable Neighbourhood Search (rVNS), greedy and random hyperheuristic approaches and other tabu search based heuristics for a complex real wor...

This paper introduces an iterated tabu search heuristic for the daily car sequencing problem in which a set of cars must be sequenced so as to satisfy requirements from the paint shop and the assembly line. The iterated tabu search heuristic combines a classical tabu search with perturbation operators that help escape from local optima. The resulting heuristic is flexible, easy to implement, an...

We presented a parallel tabu search (PTS) algorithm for the traveling salesman problem (TSP), which is NP-hard. To parallelize tabu search (TS) algorithm efficiently, the search space decomposition based on partition principle was used to balance the computing load, while exploitation in subspace had been boosted by an adaptive search strategy of intensification and diversification. Numerical r...

We describe the use of a rewriting system to determine equivalence classes over the search-space of optimisation problems. These equivalence classes may be used to derive redundant subsequences in the search-space for incorporation into metaheuristics such as backtracking, genetic algorithms and tabu-search. We use this approach as the basis for a new tabu-search variant — ‘EquationalTS’ and ap...

This paper describes an attribute based tabu search heuristic for the Generalized Minimum Spanning Tree Problem (GMSTP) known to be NP-hard. Given a graph whose vertex set is partitioned into clusters, the GMSTP consists of designing a minimum cost tree spanning all clusters. An attribute based tabu search heuristic employing new neighborhoods is proposed. An extended set of TSPLIB test instanc...

We provide an improved algorithm called “a neighborhood expansion tabu search algorithm based on genetic factors” (NETS) to solve traveling salesman problem. The algorithm keeps the traditional tabu algorithm’s neighborhood, ensure the algorithm’s strong climbing ability and go to the local optimization. At the same time, introduce the genetic algorithm’s genetic factor (crossover factor and va...

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 ...