A novel staged continuous Tabu search (SCTS) algorithm is proposed for solving global optimization problems of multi-minima functions with multi-variables. The proposed method comprises three stages that are based on the continuous Tabu search (CTS) algorithm with different neighbor-search strategies, with each devoting to one task. The method searches for the global optimum thoroughly and effi...

In the last decade, many heuristic methods have evolved for solving optimization problems that were previously difficult or impossible to solve. These methods include simulated annealing (SA), tabu search (TS), genetic algorithm (GA), differential evolution (DE), evolutionary programming (EP), evolutionary strategy (ES), ant colony optimization (ACO), and particle swarm optimization (PSO). This...

Local search techniques like simulated annealing and tabu search are based on a neighborhood structure defined on the set of feasible solutions of a discrete optimization problem. For the scheduling problems Pm )I C,,,,, 1 1 prec 1 1 Ui, and a large class of sequencing problems with precedence constraints having local interchange properties we replace a simple neighborhood by a neighborhood on ...

In. this paper: we compare the performance of three typical and widely used optimization techniques for a specific M E G source localization problem. Firstly, we introduce a hybrid algorithm by combining genetic and local search strategies t o overcome disadvantages of conventional genetic algorithms. Secondly, we apply the tabu search. a widely used optimization methods in combinational optimi...

This paper presents HAS-QAP, a hybrid ant colony system coupled with a local search, applied to the quadratic assignment problem. HAS-QAP uses pheromone trail information to perform modifications on QAP solutions, unlike more traditional ant systems that use pheromone trail information to construct complete solutions. HAS-QAP is analysed and compared with some of the best heuristics available f...

This paper deals with the generation of balanced incomplete block designs (BIBD), a hard constrained combinatorial problem with multiple applications. This problem is here formulated as a combinatorial optimization problem (COP) whose solutions are binary matrices. Two different neighborhood structures are defined, based on bit-flipping and position-swapping. These are used within three metaheu...

BIBD (balanced incomplete block design) is instrumental in design of experiments. This is usually constructed using algebraic tools such as finite projective (or affine) algebra or difference sets. Recently, heuristic algorithms have been tried, including artificial neural networks, simulated annealing, and local search method. In this paper, we present a novel approach to construct BIBDs that ...

The Annual Crop Planning (ACP) problem was a recently introduced problem in the literature. This study further expounds on this problem by presenting a new mathematical formulation, which is based on market economic factors. To determine solutions, a new local search metaheuristic algorithm is investigated which is called the enhanced Best Performance Algorithm (eBPA). eBPA's results are compar...

Abs t rac t . The goal of this paper is twofold. First, we introduce a class of local search procedures for solving optimization and constraint problems. These procedures are based on various heuristics for choosing variables and values in order to examine a general neighborhood. Second, four combinations of heuristics are empirically evaluated by using the graph-coloring problem and a real wor...