Muitiobjective pressurized water reactor reload core design by nondominated genetic algorithm search

The design of pressurized water reactor reload cores is not only a formidable optimization problem but also, in many instances, a multiobjective problem. A genetic algorithm (GA) designed to perform true multiobjective optimization on such problems is described. Genetic algorithms simulate natural evolution. They differ from most optimization techniques by searching from one group of solutions to another, rather than from one solution to another. New solutions are generated by breeding from existing solutions. By selecting better (in a multiobjective sense) solutions as parents more often, the population can be evolved to reveal the trade-off surface between the competing objectives. An example illustrating the effectiveness of this novel method is presented and analyzed. It is found that in solving a reload design problem the algorithm evaluates a similar number of loading patterns to other state-of-the-art methods, but in the process reveals much more information about the nature of the problem being solved. The actual computational cost incurred depends: on the core simulator used; the GA itself is code independent.

Standard cell automated layout for a CMOS 50 MHz 8 × 8 bit pipelined parallel dadda multiplier

An 8 × 8 pipelined parallel multiplier which uses the Dadda scheme is presented. The multiplier has been implemented in a 3-μm n-well CMOS process with two layers of metal using a standard cell automatic placement and routing program. The design uses a form of pipelined carry look-ahead adder in the final stage of summation, thus providing a significant contribution to the high performance of the multiplier. The design is expected to operate at a clock frequency of at least 50 MHz and has a flush time of seven clock cycles. The design illustrates a possible method of implementing an irregular architecture in VLSI using multiple levels of low-resistance, low-capacitance interconnect and automated layout techniques.