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Multi-parameter and multi-objective collaborative optimization of a suspended monorail vehicle addressing its strongly coupled nonlinear characteristics. [PDF]
Sci RepJiang Y, Zhang S, Liu W, Chen R, Wang Q.
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Simulated annealing algorithm with adaptive neighborhood
Applied Soft Computing Journal, 2011As we know, simulated annealing algorithm with large neighborhoods has greater probability of arriving at a global optimum than a small one has, if the other conditions, i.e., the initial configuration, initial temperature and temperature decreasing rate, are the same.
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Parallel recombinative simulated annealing: A genetic algorithm
Parallel Computing, 1995zbMATH Open Web Interface contents unavailable due to conflicting licenses.
David E Goldberg
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Parallel Simulated Annealing Algorithms
Journal of Parallel and Distributed Computing, 1996Simulated annealing (SA) has been considered a good tool for complex nonlinear optimization problems. The technique has been widely applied to a variety of problems. However, a major disadvantage of the technique is that it is extremely slow and hence not suitable for complex optimization problems such as scheduling.
D. Janaki Ram +2 more
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A parallel simulated annealing algorithm
Parallel Computing, 1993zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nicolas Boissin, Jean-Luc Lutton
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Aspiration Based Simulated Annealing Algorithm
Journal of Global Optimization, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
M. M. Ali, C. Storey
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NEW SIMULATED ANNEALING ALGORITHMS FOR CONSTRAINED OPTIMIZATION [PDF]
Asia-Pacific Journal of Operational Research, 2010 We propose a Population based dual-sequence Non-Penalty Annealing algorithm (PNPA) for solving the general nonlinear constrained optimization problem. The PNPA maintains a population of solutions that are intermixed by crossover to supply a new starting solution for simulated annealing throughout the search. Every time the search gets stuck at a local
Linet Özdamar, Chandra Sekhar Pedamallu
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A simulated annealing algorithm for demand response
2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies, 2011For many consumers there are loads which need to be on for a subinterval between two time instants, but it is immaterial during which subinterval it is run. In many price based Demand Response (DR) programs such as Time of Use (TOU), Critical Peak Pricing (CPP), Extreme Day Pricing customers are informed about the prices on a day ahead bases.
T. P. Imthias Ahamed +3 more
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