Scatter search for the vehicle routing problem with time windows

In this paper we use a scatter search framework to solve the vehicle routing problem with time windows (VRPTW). Our objective is to achieve effective solutions and to investigate the effects of reference set design parameters pertaining to size, quality and diversity. Both a common arc method and an optimization-based set covering model are used to combine vehicle routing solutions. A reactive tabu search metaheuristic and a tabu search with an advanced recovery feature, together with a set covering procedure are used for solution improvement. Our approach led to a robust solution method, generating solution quality that is competitive with the current best metaheuristics.     

Massively parallel analog tabu search using neural networks applied to simple plant location problems

Neural networks and tabu search are two very significant techniques which have emerged recently for the solution of discrete optimization problems. Neural networks possess the desirable quality of implementability in massively parallel hardware while the tabu search metaheuristic shows great promise as a powerful global search method. Tabu Neural Network (TANN) integrates an analog version of the short term memory component of tabu search with neural networks to generate a massively parallel, analog global search strategy that is hardware implementable. In TANN, both the choice of the element to enter the tabu list as well as the maintenance of the decision elements in tabu status is accomplished via neuronal activities. In this paper we apply TANN to the simple plant location problem. Comparisons with the Hopfield-Tank network show an average improvement of about 85% in the quality of solutions obtained.     

Tabu Machine: A New Neural Network Solution Approach for Combinatorial Optimization Problems

A new artificial neural network solution approach is proposed to solve combinatorial optimization problems. The artificial neural network is called the Tabu Machine because it has the same structure as the Boltzmann Machine does but uses tabu search to govern its state transition mechanism. Similar to the Boltzmann Machine, the Tabu Machine consists of a set of binary state nodes connected with bidirectional arcs. Ruled by the transition mechanism, the nodes adjust their states in order to search for a global minimum energy state. Two combinatorial optimization problems, the maximum cut problem and the independent set problem, are used as examples to conduct a computational experiment. Without using overly sophisticated tabu search techniques, the Tabu Machine outperforms the Boltzmann Machine in terms of both solution quality and computation time.     

Backbone guided tabu search for solving the UBQP problem

We propose a backbone-guided tabu search (BGTS) algorithm for the Unconstrained Binary Quadratic Programming (UBQP) problem that alternates between two phases: (1) a basic tabu search procedure to optimize the objective function as far as possible; (2) a strategy using the TS notion of strongly determined variables to alternately fix and free backbone components of the solutions which are estimated likely to share values in common with an optimal solution. Experimental results show that the proposed method is capable of finding the best-known solutions for 21 large random instances with 3000 to 7000 variables and boosts the performance of the basic TS in terms of both solution quality and computational efficiency.     

Diversification strategies in tabu search algorithms for the maximum clique problem

The purpose of this study is to develop some understanding of the benefits that can be derived from the inclusion of diversification strategies in tabu search methods. To do so, we discuss the implementation of various diversification strategies in several tabu search heuristics developed for the maximum clique problem. Computational results on a large set of randomly generated test problems are reported and compared to assess the impact of these techniques on solution quality and running time.     

A hybrid algorithm for the manufacturing cell formation problem

In this paper we compare different heuristic methods for the manufacturing cell formation problem considering part process sequence: a GRASP algorithm, a reactive GRASP algorithm and a hybrid algorithm which combines reactive GRASP and tabu search. All algorithms are tested with a set of instances from the literature. The results from the GRASP algorithm are compared to those of the reactive GRASP in order to evaluate the advantages of automatically adjusting the parameter value within the randomized greedy procedure. Also the reactive GRASP results are compared to those of the hybrid algorithm to evaluate the contribution to solution quality of replacing the local search phase of the GRASP algorithm with tabu search.     

Tabu search for graph partitioning

In this paper, we develop a tabu search procedure for solving the uniform graph partitioning problem. Tabu search, an abstract heuristic search method, has been shown to have promise in solving several NP-hard problems, such as job shop and flow shop scheduling, vehicle routing, quadratic assignment, and maximum satisfiability. We compare tabu search to other heuristic procedures for graph partitioning, and demonstrate that tabu search is superior to other solution approaches for the uniform graph partitioning problem both with respect to solution quality and computational requirements.     

An introduction to population approaches for optimization and hierarchical objective functions: A discussion on the role of tabu search

Population approaches suitable for global combinatorial optimization are discussed in this paper. They are composed of a number of distinguishable individuals called "agents", each one using a particular optimization strategy. Periods of independent search follow phases on which the population is restarted from new configurations. Due to its intrinsic parallelism and the asynchronicity of the method, it is particularly suitable for parallel computers. Results on two test problems are presented in this paper. The individual search optimization strategies for each agent have been chosen having the basic characteristics of tabu search. This has been done in order to avoid mixing the hypothesized properties of these population approaches with those of more elaborate tabu search strategies, but remarking on its main characteristics. A set of four test problem "landscapes" is discussed and their use to improve and benchmark the results by using tabu search as the individual optimization strategy within a population heuristic is suggested and explored. The application of tabu search to new problem areas, like molecular biology, is also investigated.     

An Application of Tabu Search Heuristic for the Maximum Edge-Weighted Subgraph Problem

The purpose of this article is to describe an efficient search heuristic for the Maximum Edge-weighted Subgraph (MEwS) problem. This problem requires to find a subgraph such that the sum of the weights associated with the edges of the subgraph is maximized subject to a cardinality constraint. In this study a tabu search heuristic for the MEwS problem is proposed. Different algorithms to obtain an initial solution are presented. One neighborhood search strategy is also proposed. Preliminary computational results are reported for randomly generated test problems of MEwS problem with different densities and sizes. For most of test problems, the tabu search heuristic found good solutions. In addition, for large size test problems, the tabu search outperformed the local search heuristic appearing in the literature.     

Parallel asynchronous tabu search for multicommodity location-allocation with balancing requirements

We study and compare asynchronous parallelization strategies for tabu search, and evaluate the impact on performance and solution quality of some important algorithmic design parameters: number of processors, handling of exchanged information, etc. Parallelization approaches are implemented and compared by using a tabu search algorithm for multicommodity location-allocation problems with balancing requirements.     

An effective heuristic for minimising makespan on unrelated parallel machines

Scheduling independent tasks on unrelated machines is a relatively difficult and challenging problem. In this paper, we develop a tabu search based heuristic for minimising makespan for the above problem that can provide good quality solutions for practical size problems within a reasonable amount of computational time. Our adaptation of this tabu search uses hashing to control the tabu restrictions of the search process and requires fewer critical parameters than many of the common tabu search approaches employed for combinatorial optimisation. Hashing is simple to implement and very effective in providing a near-optimal solution. Computational results are presented to demonstrate the effectiveness of the proposed heuristic.     

Evaluating the performance of tabu search procedures for flow shop sequencing

We address the problem of minimising makespan in a flow shop by using tabu search procedures. By combining different neighbourhood structures, neighbourhood examinations, and stopping conditions we obtain alternative tabu search procedures. Starting from a common initial solution we evaluate the relative performance of such procedures considering both the solution quality and computational effort.     

Query Optimization in Distributed Relational Databases

The query optimizer is the DBMS (data base management system) component whose task is to find an optimal execution plan for a given input query. Typically, optimization is performed using dynamic programming. However, in distributed execution environments, this approach becomes intractable, due to the increase in the search space incurred by distribution. We propose the use of the tabu search metaheuristic for distributed query optimization. A hashing-based data structure is used to keep track of the search memory, simplifying significantly the implementation of tabu search. To validate this proposal, we implemented the tabu search strategy in the scope of an existing optimizer, which runs several search strategies. We focus our attention on the more difficult problems in terms of the query execution space, in which the solution space includes bushy execution plans and Cartesian products, which are not dealt with very often in the literature. Using a real-life application, we show the effectiveness of tabu search when compared to other strategies.     

Simulated annealing and tabu search approaches to unidirectional flowpath design for Automated Guided Vehicle Systems

In this paper, we address the flowpath design issue of Automated Guided Vehicle Systems (AGVSs). In particular, we concentrate on the design of unidirectional flowpaths (i.e. vehicles are restricted to travel only in one direction along a given segment of the flowpath). We have developed intelligent heuristics — simulated annealing and tabu search algorithms for the design of unidirectional AGVSs. Different versions of simulated annealing and tabu search algorithms are implemented. Our extensive computational results indicate that both simulated annealing and tabu search yield solutions of adequate quality for all practical purposes. A tabu search implementation with the use of a frequency-based memory structure dominates all tested heuristics in terms of solution quality (i.e. percent deviation from optimality), with an impressive average performance over 45 test problems of less than 0.85% deviation from optimality.     

Assignment of add–drop multiplexer (ADM) rings and digital cross-connect system (DCS) mesh in telecommunication networks

This paper discusses a design of a hybrid ring–mesh network in a survivable communication network. Given a set of traffic demands, the problem is to assign each traffic demand to rings and mesh such that the cost of add–drop multiplexer (ADM) and digital cross-connect system (DCS) equipment required is minimized. This assignment problem can be considered together with the fibre routing of nodes on rings and mesh. As a solution procedure, a tabu search is developed with recency-based short-term and frequency-based long-term memory structures. In computational experiments, the proposed tabu search is compared with the solutions obtained by the branch and bound procedure of CPLEX. We see that the tabu search provides a nearly optimal solution within sufficiently short time periods for all test problems with a gap of approximately 1–4% from the lower bound.     

A hybrid tabu search based heuristic for the periodic distribution inventory problem with perishable goods

Most of the research on integrated inventory and routing problems ignores the case when products are perishable. However, considering the integrated problem with perishable goods is crucial since any discrepancy between the routing and inventory cost can double down the risk of higher obsolescence costs due to the limited shelf-life of the products. In this paper, we consider a distribution problem involving a depot, a set of customers and a homogeneous fleet of capacitated vehicles. Perishable goods are transported from the depot to customers in such a way that out-of-stock situations never occur. The objective is to simultaneously determine the inventory and routing decisions over a given time horizon such that total transportation cost is minimized. We present a new “arc-based formulation” for the problem which is deemed more suitable for our new tabu search based approach for solving the problem. We perform a thorough sensitivity analysis for each of the tabu search parameters individually and use the obtained gaps to fine-tune the parameter values that are used in solving larger sized instances of the problem. We solve different sizes of randomly generated instances and compare the results obtained using the tabu search algorithm to those obtained by solving the problem using CPLEX and a recently published column generation algorithm. Our computational experiments demonstrate that the tabu search algorithm is capable of obtaining a near-optimal solution in less computational time than the time required to solve the problem to optimality using CPLEX, and outperforms the column generation algorithm for solving the “path flow formulation” of the problem in terms of solution quality in almost all of the considered instances.     

Parallelizing Tabu Search on a Cluster of Heterogeneous Workstations

In this paper, we present the parallelization of tabu search on a network of workstations using PVM. Two parallelization strategies are integrated: functional decomposition strategy and multi-search threads strategy. In addition, domain decomposition strategy is implemented probabilistically. The performance of each strategy is observed and analyzed. The goal of parallelization is to speedup the search in finding better quality solutions. Observations support that both parallelization strategies are beneficial, with functional decomposition producing slightly better results. Experiments were conducted for the VLSI cell placement, an NP-hard problem, and the objective was to achieve the best possible solution in terms of interconnection length, timing performance (circuit speed), and area. The multiobjective nature of this problem is addressed using a fuzzy goal-based cost computation.     

Enhanced Adjacent Extreme-point Search and Tabu Search for the Minimum Concave-cost Uncapacitated Transshipment Problem

Practicable methods for optimising concave-cost, uncapacitated transshipment networks are non exact. In this paper, one such effective method, that of adjacent extreme point search, is further developed to enhance its overall computational efficiency. The enhanced search algorithm is then imbedded in a tabu search scheme which proved capable of finding better solutions, by a wide margin in some instances. Another tabu search scheme, somewhat inferior in terms of solution quality but computationally more efficient, is also developed to provide an alternative solution vehicle for larger networks. Results of extensive computational testing are included.     

Optimizing the system of virtual paths by tabu search

In an asynchronous transfer mode (ATM) network, given the network topology and traffic demands, the establishment of the system of virtual paths (VPs), and the assignment of connections to them so that the network performance is optimized, entails a number of computationally hard subproblems. The optimization problem discussed here focuses on finding a system of VP routes for a given set of VP terminators and VP capacity demands. Although it has been proven that the existing random path algorithm yields the worst case time bound, the solution performance still depends highly on the number of iterations. In this paper, an exact solution procedure and a heuristic method based on a simple tabu search have been developed for optimizing the system of VPs. Computational results show that the proposed tabu search algorithm is effective in obtaining high quality solutions, and the performance of the proposed algorithm is increasingly attractive as the problem size becomes larger.