Adaptive memory search for Boolean optimization problems

نویسندگان

  • Lars Magnus Hvattum
  • Arne Løkketangen
  • Fred Glover
چکیده

We describe a simple adaptive memory search method for Boolean Optimization Problems. The search balances the level of infeasibility against the quality of the solution, and uses a simple dynamic tabu search mechanism. Computational results on a portfolio of test problems taken from the literature are reported, showing very favorable results, both in terms of search speed and solution quality.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

New Heuristics and Adaptive Memory Procedures for Boolean Optimization Problems

We describe new constructive and iterative search methods for Boolean Optimization Problems. Extending previous work by the authors, we describe the use of adaptive clause weights and probabilistic move acceptance for the adaptive memory search. We also describe how the use of the tabu search notions of persistent attractiveness measures and marginal conditional validity as search guidance mech...

متن کامل

PSEUDO-RANDOM DIRECTIONAL SEARCH: A NEW HEURISTIC FOR OPTIMIZATION

Meta-heuristics have already received considerable attention in various fields of engineering optimization problems. Each of them employes some key features best suited for a specific class of problems due to its type of search space and constraints. The present work develops a Pseudo-random Directional Search, PDS, for adaptive combination of such heuristic operators. It utilizes a short term...

متن کامل

Comparisons of Commercial MIP Solvers and an Adaptive Memory (Tabu Search) Procedure for a Class of 0-1 Integer Programming Problems

The Boolean optimization problem (BOOP) is a highly useful formulation that embraces a variety of 0-1 integer programming problems, including weighted versions of covering, partitioning and maximum satisfiability problems. Several years ago Hvattum, Løkketangen and Glover (2006) introduced an adaptive memory (tabu search) method for BOOP which proved effective compared to competing approaches. ...

متن کامل

A limited memory adaptive trust-region approach for large-scale unconstrained optimization

This study concerns with a trust-region-based method for solving unconstrained optimization problems. The approach takes the advantages of the compact limited memory BFGS updating formula together with an appropriate adaptive radius strategy. In our approach, the adaptive technique leads us to decrease the number of subproblems solving, while utilizing the structure of limited memory quasi-Newt...

متن کامل

Parallel Random Search Algorithm for Large-Scale Constrained Pseudo-Boolean Optimization Problems

Random search methods are successfully implemented for variety of discrete optimization NP-hard problems when any exact solution approaches cannot be implemented due to large computational demands. Initially designed for unconstrained optimization, the probability changing method gives an approximate solution for various linear and non-linear pseudo-Boolean optimization problems with constraint...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Discrete Applied Mathematics

دوره 142  شماره 

صفحات  -

تاریخ انتشار 2004