This paper proposes an iterative parallel genetic algorithm with biased initial population to solve large-scale combinatorial optimization problems. The proposed scheme employs a master-slave collaboration in which the master node manages searched space of slave nodes and assigns seeds to generate initial population to slaves for their restarting of evolution process. Our approach allows us as widely as possible to search by all the slave nodes in the beginning period of the searching and then focused searching by multiple slaves on a certain spaces that seems to include good quality solutions. Computer experiment shows the effectiveness of our proposed scheme.

In this work we give an extension of Kauffman's NK-Landscapes to multiobjective MNK-Landscapes in order to study the effects of epistasis on the performance of multiobjective evolutionary algorithms (MOEAs). This paper focuses on the development of multiobjective random one-bit climbers (moRBCs). We incrementally build several moRBCs and analyze basic working principles of state of the art MOEAs on landscapes of increased epistatic complexity and number of objectives. We specially study the effects of Pareto dominance, non-dominance, and the use of memory and a population to influence the search. We choose an elitist non-dominated sorting multiobjective genetic algorithm (NSGA-II) as a representative of the latest generation of MOEAs and include its results for comparison. We detail the behavior of the climbers and show that population based moRBCs outperform NSGA-II for all values of M and K.

In this paper, CDMA slotted ALOHA system with finite size of buffers is proposed. To analyze the system performance, we use the linear approximate solution based on restricted occupancy urn models. We evaluate the system performance in terms of throughput, average delay, and rejection probability and clarify the effect of buffer capacity.

Impact ionization () in two n+-n--n+ device structures is investigated. Data obtained from self-consistent Monte-Carlo (SCMC) simulations of the devices is used to show that the average energy () of only those high energy electrons contributing to is an appropriate variable for the modeling of . A transport model allowing one to calculate is derived from the Boltzmann transport equation (BTE) and calibrated by the SCMC simulation results. The values of and the coefficient, αii, predicted by the proposed model are in good agreement with the Monte-Carlo data.