New Rollout Algorithms for Combinatorial Optimization Problems

Rollout algorithms are new computational approaches used to determine near-optimal solutions for deterministic and stochastic combinatorial optimization problems. They are built on a generic base heuristic with the aim to construct another hopefully improved heuristic. However, rollout algorithms can be very expensive from the computational point of view, so their use for practical applications can be limited. In this article, we propose modified versions of the rollout algorithms to solve deterministic optimization problems, defined in such a way to limit the computational cost, without worsening the quality of the final approximate solution obtained.

[1]  Egon Balas,et al.  The Shifting Bottleneck Procedure for Job Shop Scheduling , 1988 .

[2]  Richard Bellman,et al.  The Job-shop Scheduling Problem , 1982 .

[3]  Andrew W. Moore,et al.  Learning evaluation functions for global optimization , 1998 .

[4]  David S. Johnson,et al.  Data structures for traveling salesmen , 1993, SODA '93.

[5]  Nicola Secomandi,et al.  Exact and heuristic dynamic programming algorithms for the vehicle routing problem with stochastic demands , 1998 .

[6]  W. Press,et al.  Numerical Recipes in Fortran: The Art of Scientific Computing.@@@Numerical Recipes in C: The Art of Scientific Computing. , 1994 .

[7]  Gerhard Reinelt,et al.  TSPLIB - A Traveling Salesman Problem Library , 1991, INFORMS J. Comput..

[8]  Mauricio G. C. Resende,et al.  Designing and reporting on computational experiments with heuristic methods , 1995, J. Heuristics.

[9]  Wei Zhang,et al.  A Reinforcement Learning Approach to job-shop Scheduling , 1995, IJCAI.

[10]  Andrew G. Barto,et al.  Improving Elevator Performance Using Reinforcement Learning , 1995, NIPS.

[11]  John N. Tsitsiklis,et al.  Neuro-Dynamic Programming , 1996, Encyclopedia of Machine Learning.

[12]  William H. Press,et al.  Numerical recipes in C (2nd ed.): the art of scientific computing , 1992 .

[13]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[14]  Gerald Tesauro,et al.  TD-Gammon, a Self-Teaching Backgammon Program, Achieves Master-Level Play , 1994, Neural Computation.

[15]  Nicola Secomandi,et al.  Comparing neuro-dynamic programming algorithms for the vehicle routing problem with stochastic demands , 2000, Comput. Oper. Res..

[16]  Dimitri P. Bertsekas,et al.  Rollout Algorithms for Stochastic Scheduling Problems , 1999, J. Heuristics.

[17]  John N. Tsitsiklis,et al.  Rollout Algorithms for Combinatorial Optimization , 1997, J. Heuristics.