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M.K. Yang, C.R. Das, "Evaluation of a Parallel BranchandBound Algorithm on a Class of Multiprocessors," IEEE Transactions on Parallel and Distributed Systems, vol. 5, no. 1, pp. 7486, January, 1994.  
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@article{ 10.1109/71.262590, author = {M.K. Yang and C.R. Das}, title = {Evaluation of a Parallel BranchandBound Algorithm on a Class of Multiprocessors}, journal ={IEEE Transactions on Parallel and Distributed Systems}, volume = {5}, number = {1}, issn = {10459219}, year = {1994}, pages = {7486}, doi = {http://doi.ieeecomputersociety.org/10.1109/71.262590}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Parallel and Distributed Systems TI  Evaluation of a Parallel BranchandBound Algorithm on a Class of Multiprocessors IS  1 SN  10459219 SP74 EP86 EPD  7486 A1  M.K. Yang, A1  C.R. Das, PY  1994 KW  Index Termsmultiprocessor interconnection networks; multiprocessing systems; parallel algorithms;performance evaluation; parallel branchandbound algorithm; MINbased multiprocessorsystems; probabilistic model; serial bestfirst search; conflictfree mapping scheme;communication overheads; computation overheads VL  5 JA  IEEE Transactions on Parallel and Distributed Systems ER   
We propose and evaluate a parallel "decomposite bestfirst" search branchandboundalgorithm (dbs) for MINbased multiprocessor systems. We start with a new probabilisticmodel to estimate the number of evaluated nodes for a serial bestfirst searchbranchandbound algorithm. This analysis is used in predicting the parallel algorithmspeedup. The proposed algorithm initially decomposes a problem into N subproblems,where N is the number of processors available in a multiprocessor. Afterwards, eachprocessor executes the serial bestfirst search to find a local feasible solution. Localsolutions are broadcasted through the network to compute the final solution. Aconflictfree mapping scheme, known as the stepbystep spread, is used for subproblemdistribution on the MIN. A speedup expression for the parallel algorithm is then derivedusing the serial bestfirst search node evaluation model. Our analysis considers bothcomputation and communication overheads for providing realistic speedup.Communication modeling is also extended for the parallel global bestfirst searchtechnique. All the analytical results are validated via simulation. For large systems, whencommunication overhead is taken into consideration, it is observed that the paralleldecomposite bestfirst search algorithm provides better speedup compared to otherreported schemes.
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