INFORMS Journal on Computing current issue

From the Editor

Chinneck, J. W. — Sat, 07 Nov 2009 10:01:27 PST

No abstract available.

State-of-the Art Review--Evolutionary Algorithms for Vehicle Routing

Potvin, J.-Y. — Sat, 07 Nov 2009 10:01:27 PST

This paper is a survey of the literature on applications of evolutionary algorithms for vehicle routing problems. It reports on genetic algorithms, evolution strategies, and particle swarm optimization when applied to the classical capacitated vehicle routing problem and many of its variants. The performance of evolutionary algorithms is also compared with the best alternative problem-solving approaches on benchmark instances.

A Constraint Programming Approach for Solving a Queueing Design and Control Problem

Terekhov, D., Beck, J. C., Brown, K. N. — Sat, 07 Nov 2009 10:01:27 PST

A facility with frontroom and backroom operations has the option of hiring specialized or cross-trained workers. Cross-trained workers can be switched between the two rooms depending on demand but are more expensive than specialized ones. Assuming stochastic customer arrival and service times, we seek a smallest-cost combination of cross-trained and specialized workers, together with a policy for switching the cross-trained workers between the rooms, which satisfies constraints on the expected customer waiting time and expected number of workers in the back room. A constraint programming approach using logic-based Benders' decomposition is presented. Experimental results demonstrate the strong performance of this approach across a wide variety of problem parameters. This paper provides one of the first links between queueing optimization problems and constraint programming.

An Exact Method for the Minimum Cardinality Problem in the Treatment Planning of Intensity-Modulated Radiotherapy

Ernst, A. T., Mak, V. H., Mason, L. R. — Sat, 07 Nov 2009 10:01:27 PST

In this paper, we introduce an exact method based on constraint programming ideas for a combinatorial optimization problem that arises from the treatment planning of intensity-modulated radiotherapy—the minimum cardinality problem (MCP). The MCP is to find a decomposition of a given integer matrix into a weighted sum of binary matrices with consecutive ones, such that the number of such binary matrices is minimised. We compare our method with two recent exact methods for the same problem and a recent exact method for a special case of the problem. Numerical results are presented that indicate that our method is computationally more efficient than the three existing methods.

An Encoding in Metaheuristics for the Minimum Communication Spanning Tree Problem

Rothlauf, F. — Sat, 07 Nov 2009 10:01:27 PST

Problem-specific encodings can improve the performance of metaheuristics, such as genetic algorithms or simulated annealing. This paper studies the link-biased (LB) encoding, which is a tree representation, and applies metaheuristics using this encoding to the minimum communication spanning tree (MCST) problem. Given the communication requirements of the nodes, the MCST problem seeks a communication spanning tree with minimum total cost. Optimal solutions for MCST problems are similar to minimum spanning trees (MSTs), and the LB encoding exploits this property by encoding trees similar to MSTs with higher probability. The paper investigates how to systematically design problem-specific encodings for MCST problems and how to set the encoding-specific parameter that controls the bias of the LB encoding towards MSTs; it then presents performance results for various MCST problems.

On the Integrated Production and Distribution Problem with Bidirectional Flows

Lei, L., Zhong, H., Chaovalitwongse, W. A. — Sat, 07 Nov 2009 10:01:27 PST

The integrated production and distribution problem with bidirectional flows is a complicated optimization problem, usually with large problem sizes when encountered in practice. In this study, we propose a partial linear programming relaxation-based heuristic approach to solve a variation of this problem. The approach is called a partial relaxation in the sense that it relaxes the integer requirements only on selected variables. We also report on the gaps between the optimal solution and the heuristic solution provided by this partial relaxation, including analytical gaps for a special case and empirical gaps for randomly generated test cases. Our study of this problem was motivated by the operational planning problem of a medical equipment leasing network that involves a forward flow for new and refurbished devices and a reverse flow for used devices to be returned to suppliers over a multiple time-period planning horizon.

The Knowledge-Gradient Policy for Correlated Normal Beliefs

Frazier, P., Powell, W., Dayanik, S. — Sat, 07 Nov 2009 10:01:27 PST

We consider a Bayesian ranking and selection problem with independent normal rewards and a correlated multivariate normal belief on the mean values of these rewards. Because this formulation of the ranking and selection problem models dependence between alternatives' mean values, algorithms may use this dependence to perform efficiently even when the number of alternatives is very large. We propose a fully sequential sampling policy called the knowledge-gradient policy, which is provably optimal in some special cases and has bounded suboptimality in all others. We then demonstrate how this policy may be applied to efficiently maximize a continuous function on a continuous domain while constrained to a fixed number of noisy measurements.

An Algorithm and a Core Set Result for the Weighted Euclidean One-Center Problem

Kumar, P., Yildirim, E. A. — Sat, 07 Nov 2009 10:01:27 PST

Given a set A of m points in n-dimensional space with corresponding positive weights, the weighted Euclidean one-center problem, which is a generalization of the minimum enclosing ball problem, involves the computation of a point c_A Rⁿ that minimizes the maximum weighted Euclidean distance from c_A to each point in A. In this paper, given > 0, we propose and analyze an algorithm that computes a (1 + )-approximate solution to the weighted Euclidean one-center problem. Our algorithm explicitly constructs a small subset X A, called an -core set of A, for which the optimal solution of the corresponding weighted Euclidean one-center problem is a close approximation to that of A. In addition, we establish that | X| depends only on and on the ratio of the smallest and largest weights, but is independent of the number of points m and the dimension n. This result subsumes and generalizes the previously known core set results for the minimum enclosing ball problem. Our algorithm computes a (1 + )-approximate solution to the weighted Euclidean one-center problem for A in O(mn|X|) arithmetic operations. Our computational results indicate that the size of the -core set computed by the algorithm is, in general, significantly smaller than the theoretical worst-case estimate, which contributes to the efficiency of the algorithm, especially for large-scale instances. We shed some light on the possible reasons for this discrepancy between the theoretical estimate and the practical performance.

Transforming Renewal Processes for Simulation of Nonstationary Arrival Processes

Gerhardt, I., Nelson, B. L. — Sat, 07 Nov 2009 10:01:27 PST

Simulation models of real-life systems often assume stationary (homogeneous) Poisson arrivals. Therefore, when nonstationary arrival processes are required, it is natural to assume Poisson arrivals with a time-varying arrival rate. For many systems, however, this provides an inaccurate representation of the arrival process that is either more or less variable than Poisson. In this paper we extend techniques that transform a stationary Poisson arrival process into a nonstationary Poisson arrival process (NSPP) by transforming a stationary renewal process into a nonstationary, non-Poisson (NSNP) arrival process. We show that the desired arrival rate is achieved and that when the renewal base process is either more or less variable than Poisson, then the NSNP process is also more or less variable, respectively, than an NSPP. We also propose techniques for specifying the renewal base process when presented properties of, or data from, an arrival process and illustrate them by modeling real arrival data.

Numerically Safe Gomory Mixed-Integer Cuts

Cook, W., Dash, S., Fukasawa, R., Goycoolea, M. — Sat, 07 Nov 2009 10:01:27 PST

We describe a simple process for generating numerically safe cutting planes using floating-point arithmetic and the mixed-integer rounding procedure. Applying this method to the rows of the simplex tableau permits the generation of Gomory mixed-integer cuts that are guaranteed to be satisfied by all feasible solutions to a mixed-integer programming problem (MIP). We report on tests with the MIPLIB 3.0 and MIPLIB 2003 test collections as well as with MIP instances derived from the TSPLIB traveling salesman library.

Appreciation to Referees

Chinneck, J. W. — Sat, 07 Nov 2009 10:01:27 PST

On behalf of the Editorial Board, I would like to thank the following people, who acted as Referees during the past year.

Author Index

Sat, 07 Nov 2009 10:01:27 PST

No abstract available.

Key Word Index

Sat, 07 Nov 2009 10:01:27 PST

No abstract available.