Tabu search is a "higher level" heuristic procedure for solving optimization problems, designed to guide other methods (or their component processes) to escape the trap of local optimality. Tabu search has obtained optimal and near optimal solutions to a wide variety of classical and practical problems in applications ranging from scheduling to telecommunications and from character recognition ...

This paper introduces a parallel iterated tabu search heuristic for solving four different routing problems: the classical vehicle routing problem (VRP), the periodic VRP, the multi-depot VRP, and the site-dependent VRP. In addition, it is applicable to the time-window constrained variant of these problems. Using the iterated local search framework, the heuristic combines tabu search with a sim...

Tabu search is a meta-heuristic approach that is found to be useful in solving combinatorial optimization problems. We implement the adaptive memory features of tabu search to align multiple sequences. Adaptive memory helps the search process to avoid local optima and explores the solution space economically and effectively without getting trapped into cycles. The algorithm is further enhanced ...

We develop a new hybrid tabu search method for optimizing a continuous diieren-tiable function over the extreme points of a polyhedron. The method combines extreme point tabu search with traditional descent algorithms based on linear programming. The tabu search algorithm utilizes both recency-based and frequency-based memory and oscillates between local improvement and diversiication phases. T...

The purpose of this paper is to describe the implementation and testing of the tabu cycle method and two variants of the conditional probability method. These methods were originally described in Glover and Laguna (1997) but have been largely ignored in the tabu search literature. For the purpose of testing, we employ a singleattribute implementation of a short-term memory procedure for the sol...

This study considers production planning problems involving multiple products, multiple resources, multiple periods, setup times, and setup costs. It can be formulated as a mixed integer program (MIP). Solving a realistic MIP production planning problem is NP-hard; therefore, we use tabu search methods to solve such a difficult problem. Furthermore, we improve tabu search by a new candidate lis...

Tabu search is one of the most effective heuristics for locating high-quality solutions to a diverse array of NP-hard combinatorial optimization problems. Despite the widespread success of tabu search, researchers have a poor understanding of many key theoretical aspects of this algorithm, including models of the high-level run-time dynamics and identification of those search space features tha...

The goal of this paper is to discuss the tabu search (TS) meta-heuristic and its enhancement for combinatorial optimization problems. Firstly, the issues related to the principles and specific features of the standard TS are concerned. Further, a promising extension to the classical tabu search scheme is introduced. The most important component of this extension is a special kind of diversifica...

The reload cost spanning tree problem (RCSTP) is an NP-hard problem, where we are given a set of nonnegative pairwise demands between nodes, each edge is colored and a reload cost is incurred when a color change occurs on the path between a pair of demand nodes. The goal is to find a spanning tree with minimum reload cost. We propose a tree-nontree edge swap neighborhood for the RCSTP and an ef...

Some studies have been recently carried out to investigate the use of search-based techniques in estimating software development effort and the results reported seem to be promising. Tabu Search is a meta-heuristic approach successfully used to address several optimization problems. In this paper, we report on an empirical analysis carried out exploiting Tabu Search on two publicly available da...