The method to handle the constraints is the key factor to success when we are trying to solve constrained optimization problems by quantum-behaved particle swarm optimization. In this paper, a modified quantumbehaved particle swarm optimization is proposed for constrained optimization. Double fitness values are defined for every particle. Whether the particle is better or not will be decided by its two fitness values. An adaptive strategy to keep a fixed proportion of infeasible particles is used in this method. Experimental results show that the modified algorithm is feasible and better on precision and convergence than quantum-behaved particle swarm optimization using a penalty function and other optimization algorithms.

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Computational science and engineering is an emerging and promising discipline in shaping future research and development activities in academia and industry, in fields ranging from engineering, science, finance, and economics, to arts and humanities. New challenges arise in the modelling of complex systems, sophisticated algorithms, advanced scientific and engineering computing and associated (multidisciplinary) problem-solving environments. IJCSE addresses the state of the art of all aspects of computational science and engineering, highlighting computational methods and techniques for science and engineering applications.

This paper proposes a three-dimensional (3D) controlled quantum teleportation scheme for an unknown single-qutrit state. The scheme is first introduced in an ideal environment, and its detailed implementation is described via the transformation of the quantum system. Four types of 3D-Pauli-like noise corresponding to Weyl operators are created by Kraus operators: trit-flip, t-phase-flip, trit-phase-flip, and t-depolarizing. Then, this scheme is analyzed in terms of four types of noisy channel with memory. For each type of noise, the average fidelity is calculated as a function of memory and noise parameters, which is afterwards compared with classical fidelity. The results demonstrate that for trit-flip and t-depolarizing noises, memory will increase the average fidelity regardless of the noise parameter. However, for t-phase-flip and trit-phase-flip noises, memory may become ineffective in increasing the average fidelity above a certain noise threshold.