Formalizing nonmonotonic reasoning systems
Artificial Intelligence
Parallel branch and bound algorithms on hypercube multiprocessors
C3P Proceedings of the third conference on Hypercube concurrent computers and applications - Volume 2
Parallel dynamic interaction--an inherently parallel problem-solving methodology
Parallel dynamic interaction--an inherently parallel problem-solving methodology
Parallel Simulated Annealing Algorithms for Cell Placement on Hypercube Multiprocessors
IEEE Transactions on Parallel and Distributed Systems
Parallel Coarse Grain Computing of Boltzmann Machines
Neural Processing Letters
On Parallelizing the Multiprocessor Scheduling Problem
IEEE Transactions on Parallel and Distributed Systems
Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
State of the Art in Parallel Search Techniques for Discrete Optimization Problems
IEEE Transactions on Knowledge and Data Engineering
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The class of NP-hard problems contains many problems of considerable practical importance. The complexity of these problems is so overwhelming that exhaustive search of the solution space is not possible even using massively parallel search techniques, particularly for problems of super-exponential complexity such as flow-shop and job-shop scheduling. This two-part paper discusses a novel, inherently parallel heuristic solution technique. Part I presents this technique, known as Parallel Dynamic Interaction (PDI), as a general solution framework that is applicable to a number of computationally intractable problems, and gives details of its general methodology.From a parallel processing standpoint, PDI is interesting because it is inherently based upon the dynamic interplay between simultaneously executing subproblems. As such, PDI has no direct serial analog, and is not directly amenable to conventional parallel processing speedup analysis. This may provide an indication that parallel processing can offer opportunities beyond simply speeding up the solution of sequentially specified algorithms. From a practical problem-solving perspective, PDI shows promise as a method capable of generating high quality solutions to exponentially and super-exponentially hard problems. For large problems, PDI is often able to find a near-optimal solution many orders of magnitude faster than the time taken for a conventional parallel branch-and-bound search to find a solution of comparable quality. The successful application of PDI to three NP-hard problems is described in Part II of this paper.