An introduction to parallelism in combinatorial optimization
Discrete Applied Mathematics
Integer and combinatorial optimization
Integer and combinatorial optimization
Optimal solution of set covering/partitioning problems using dual heuristics
Management Science
Large-scale 0-1 linear programming on distributed workstations
Annals of Operations Research
Parallel algorithms for the set covering problem
Parallel algorithms for the set covering problem
Results from a parallel branch and bound algorithm for the asymmetric traveling salesman problem
Operations Research Letters
Simulating realistic set covering problems with known optimal solutions
Computers and Industrial Engineering
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We discuss the results of computational experiments using a new parallel multi-task model for integer optimization. The model is implemented in C on a BBN TC2000 computer. Eight branch-and-bound algorithms based on the use of two types of tasks, linear programming and subgradient optimization with Lagrangian relaxation, are tested on difficult randomly generated set covering problems. We investigate the influence of relaxation choice and node selection strategy on parallel performance. Results indicate that the Lagrangian relaxation using a mixed selection strategy is effective on the largest problems. The best overall algorithms divide the computer resources into two distinct searches, which communicate only to update global information on lower and upper bounds.