Efficient heuristic algorithms for positive 0-1 polynomial programming problems

Journal Article · Thu Jul 01 04:00:00 EDT 1982 · Manage. Sci.; (United States)

DOI:https://doi.org/10.1287/mnsc.28.7.829· OSTI ID:5214158

Granot, F

Develops two types of heuristic methods for solving the positive 0-1 polynomial programming (PP) problem of finding a 0-1 vector x that maximizes c/sup t/x subject to f(x)>b where c, b>0 and f is an m-vector of polynomials with nonnegative coefficients. The various heuristics were first tested on randomly generated sparse problems of up to 50 variables and 50 constraints, and their performance in terms of computational time and effectiveness was investigated. The results were very encouraging. Optimal solutions were consistently obtained by some of the heuristic methods in over 50 percent of the problems solved. The effectiveness was on the average better than 99 percent and no less than 96.5 percent . The computational time using these heuristics is on the average 5 percent of the time required to solve the PP problems to optimality. Some results for very sparse problems with up to 1000 variables and 200 constraints are also reported. 23 references.

• Research Organization: Univ. of British Columbia, Vancouver, Canada
• OSTI ID: 5214158
• Journal Information: Manage. Sci.; (United States), Journal Name: Manage. Sci.; (United States) Vol. 7; ISSN MSCIA
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
990200* -- Mathematics & Computers
ALGORITHMS
FUNCTIONS
MATHEMATICAL LOGIC
POLYNOMIALS
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