Solving combinatorial optimization problems can often lead to runtime growing exponentially as a function of the input size. But important real-world problems, industrial applications, and academic research challenges, may demand exact optimal solutions. In such situations, parallel processing can reduce the runtime from days or months, typical when one workstation is used, to a few minutes or even seconds. Partners of the CEC-sponsored SCOOP Project (Solving Combinatorial Optimization Problems in Parallel) contributed, on invitation, to this book; much attention was paid to competent...
Solving combinatorial optimization problems can often lead to runtime growing exponentially as a function of the input size. But important real-world ...
