Variable Search Research Articles

Nurse scheduling with tabu search and strategic oscillation

The problem of producing rosters for nursing staff in a large general hospital is tackled using tabu search with strategic oscillation. The objective is to ensure that enough nurses are on duty at all times while taking account of individual preferences and requests for days off in a way that is seen to treat all employees fairly. This is achieved using a variant of tabu search which repeatedly oscillates between finding a feasible cover, and improving it in terms of preference costs. Within each phase the search is controlled by a combination of different neighbourhoods and candidate lists designed to aggressively seek out local optima and then to react to the problems encountered on arrival. The result is a robust and effective method which is able to match the quality of solutions produced by a human expert.

Multiple-facility loading under capacity-based economies of scope

Multiple-facility loading (MFL) involves the allocation of products among a set of finite-capacity facilities. Applications of MFL arise naturally in a variety of production scheduling environments. MFL models typically assume that capacity is consumed as a linear function of products assigned to a facility. Product similarities and differences, however, result in capacity-based economies or diseconomies of scope, and thus the effective capacity of the facility is often a (nonlinear) function of the set of tasks assigned to the facility. This article addresses the multiple-facility loading problem under capacity-based economies (and diseconomies) of scope (MFLS). We formulate MFLS as a nonlinear 0–1 mixed-integer programming problem, and we discuss some useful properties. MFLS generalizes many well-known combinatorial optimization problems, such as the capacitated facility location problem and the generalized assignment problem. We also define a tabu-search heuristic and a branch-and-bound algorithm for MFLS. The tabu-search heuristic alternates between two search phases, a regional search and a diversification search, and offers a novel approach to solution diversification. We also report computational experience with the procedures. In addition to demonstrating MFLS problem tractability, the computational results indicate that the heuristic is an effective tool for obtaining high-quality solutions to MFLS. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 229–256, 1997

New linear time algorithms for generating perfect elimination orderings of chordal graphs

We propose two linear time algorithms: maximum cardinality depth-first search (MCDFS) and maximum cardinality breadth-first search (MCBFS), which are variants of depth-first search and breadth-first search, respectively, to generate perfect elimination orderings of chordal graphs.

Heuristics for biquadratic assignment problems and their computational comparison

The biquadratic assignment problem (BiQAP) is a generalization of the quadratic assignment problem (QAP). As for any hard optimization problem also for BiQAP, a reasonable effort to cope with the problem is trying to derive heuristics which solve it suboptimally and which, possibly, yield a good trade off between the solution quality and the time and memory requirements. In this paper we describe several heuristics for BiQAPs, in particular pair exchange algorithms (improvement methods) and variants of simulated annealing and taboo search. We implement these heuristics as C codes and analyze their performances.

A Tabu Search Algorithm for the Resource-Constrained Assignment Problem

Efficient algorithms are availabe to solve the unconstrained assignment problem. However, when resource or budgetary restrictions are imposed, the problem becomes difficult to solve. We consider such a resource-constrained assignment problem and present a tabu search heuristic to solve it. Extensive computational results are presented which establish the superiority of the proposed algorithm over the existing algorithms. Our adaptation of tabu search uses strategic oscillation, randomized short-term memory and multiple start as a means of search diversification.

Extensions of a tabu search adaptation to the quadratic assignment problem

The adaptation of tabu search to the Quadratic Assignment Problem (QAP) is refined by incorporating knowledge about permutations yielding good objective function values into the solution process. This knowledge serves two purposes. First, it is used to guide the nonimproving moves toward targeted “good” permutations. Second, it allows the possibility to restrict search in the solution space by fixing those parts of permutations that are common in good quality solutions. Fixing and freeing parts of permutations provides an interplay between intensification and diversification of search. Restricting the search neighborhood becomes essential in solution attempts for QAPs of larger dimensions due to the increase in computational time. Computational results for QAPs of dimension 100 are very promising. An implementation of the approach to dynamic tabu list sizes that creates “moving gaps” in the tabu list is also described. Combining these ingredients, the method obtains very good results for all Skorin-Kapov's problems of dimensions 42–90.

On the heuristic solution of the permutation flow shop problem by path algorithms

In this paper we consider the classical permutation flow shop problem from machine scheduling. The problem is NP-hard. Therefore, methods such as local search or simulated annealing are often applied for the heuristic solution. In this paper we develop fast iterative methods which generate a restricted number of paths in a particular neighbourhood represented by a special shift graph. To generate the paths, we use several structural properties with respect to the path structure of a feasible solution (i.e. the longest path in a network and lower bounds resulting from this path structure). This makes the algorithm very efficient. A comparison with other well-known methods is made. The proposed algorithm also out performs different variants of simulated annealing and tabu search.

Identification of time-varying structural dynamic systems - An artificial intelligence approach

An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.

Tabu Search Applied to the Quadratic Assignment Problem

This paper describes an adaptation of Tabu Search, a recent technique to overcome local optimality, to the Quadratic Assignment Problem (QAP). Computational experiments with different parameter values and different strategies have been performed for some QAPs from the literature and some randomly generated QAPs of dimensions varying between 42 and 90. The method is implemented in a flexible form which allows the user to interact and change the parameters (tabu list size, the iteration limit, a search diversification parameter and the number of new starting solutions) during the run. The results suggest that good tabu list sizes increase with dimension of the problem. The algorithm appears to be a very efficient method for QAPs: for the standard problems tested, the best known solutions were obtained using less CPU time than previously reported in the literature. For Steinberg's problem (n = 36) with rectangular distances, a better solution than previously known in the literature was obtained. In addition, in comparison with simulated annealing, tabu search appears to be superior with respect to the solution quality. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.

講座 これからの情報担当者 第５回 多様化するオンライン検索システムへの対処

情報量が増大し, 情報媒体も多様化しているInformation anxietyの社会状況において, 企業における情報要求も複雑化, 多面化しつつある。サーチャーは, 情報のありかを探し当てることが業務であるが, 増え続けるデータベースと, 搭載するシステムの機能を見極め, どのデータベースを, どのデータベースシステムで利用すれば, 信頼のおける情報が引き出せるかを決めなければならない。商用データベースが定着し, 利用人口が増加する中で, 90年代におけるサーチャーの役割は, 検索者ではなく, 情報コンサルタントとしての役割へと移ってゆく傾向を述べる。

Task-hemispheric integrity in dual task performance

A condition of task hemispheric integrity is predicted to result in a dual task situation when the central processing and response components of each task are associated exclusively with a given cerebral hemisphere. The prediction that this condition will generate more efficient time-sharing is tested in a series of four experiments. In experiment 1 the prediction is confirmed when a spatial (tracking) and verbal (letter memory search) task are time-shared, and the hand assignment to task responses is manipulated. In experiment 2 a spatial variant of the memory search is used instead of the verbal letter search, and hand assignment effects are not obtained, since when two spatial tasks are time-shared an integrity assignment is impossible. Experiment 3 validates the hemispheric lateralization of the two single task variants of the memory search task, while experiment 4 establishes the separate “spatial’ and “verbal” resource demands of the two variants by observing their differential interference with concurrent spatial and verbal tasks.

Prompt nuclear analysis in thick samples with charged particles: The validity of Bragg’s law for range correction

The determination of fluorine in the fluorides of 31 elements by prompt analysis using the reactions (α, p0), (α, α1), (α, n1γ) and (α, p1γ) on19F was carried out in a search for discrepancies that could point to molecular effects in range corrections. Data for each reaction were normalised and normalisation factors were compared. The results for each compound were in good agreement, but intercomparison showed that the accuracy of stopping power data and the applicability of Bragg’s Law were acceptable within ±8%.

More on Min-Max Allocation

In a preceding paper Jacobsen [Jacobsen, S. 1971. On marginal allocation in single constraint min-max problems. Management Sci. (July).] shows that marginal allocation solves a class of discrete, single constraint, min-max allocation problems. A dual approach, to this problem is presented, based on a generalization of Jacobsen's P condition, which should prove more efficient when many marginal improvement iterations would be required. A variant of sequential search by bisection is applied, possibly augmented by an accelerated marginal allocation scheme, in which finite convergence to an optimum solution is guaranteed.

Time Delay in Minimax Optimization of Unimodal Functions of One Variable

A minimax search plan is developed for locating the maximum of a one dimensional unimodal function when a time delay occurs between the placement of an experiment and the result. The optimal search plans, among all the plans which place only one experiment at each unit of time, are determined for time delays of one and two periods. These plans are optimal in the sense that for a required final interval of uncertainty, they have the largest possible starting interval. Discrete variable (lattice) versions of these plans are also given, as well as plans for when the number of experiments is unknown initially. When more than one experiment can be made at each unit of time, a variant of block search is more efficient.