An improved ant colony optimization for scheduling identical parallel batching machines with arbitrary job sizes

In this paper we consider the problem of scheduling parallel batching machines with jobs of arbitrary sizes. The machines have identical capacity of size and processing velocity. The jobs are processed in batches given that the total size of jobs in a batch cannot exceed the machine capacity. Once a batch starts processing, no interruption is allowed until all the jobs are completed. First we present a mixed integer programming model of the problem. We show the computational complexity of the problem and optimality properties. Then we propose a novel ant colony optimization method where the Metropolis Criterion is used to select the paths of ants to overcome the immature convergence. Finally, we generate different scales of instances to test the performance. The computational results show the effectiveness of the algorithm, especially for large-scale instances.     

PREACO: A fast ant colony optimization for codebook generation

This paper presents an effective and efficient method for speeding up ant colony optimization (ACO) in solving the codebook generation problem. The proposed method is inspired by the fact that many computations during the convergence process of ant-based algorithms are essentially redundant and thus can be eliminated to boost their convergence speed, especially for large and complex problems. To evaluate the performance of the proposed method, we compare it with several state-of-the-art metaheuristic algorithms. Our simulation results indicate that the proposed method can significantly reduce the computation time of ACO-based algorithms evaluated in this paper while at the same time providing results that match or outperform those ACO by itself can provide.     

Ant colony optimization with immigrants schemes for the dynamic travelling salesman problem with traffic factors

Traditional ant colony optimization (ACO) algorithms have difficulty in addressing dynamic optimization problems (DOPs). This is because once the algorithm converges to a solution and a dynamic change occurs, it is difficult for the population to adapt to a new environment since high levels of pheromone will be generated to a single trail and force the ants to follow it even after a dynamic change. A good solution to address this problem is to increase the diversity via transferring knowledge from previous environments to the pheromone trails using immigrants schemes. In this paper, an ACO framework for dynamic environments is proposed where different immigrants schemes, including random immigrants, elitism-based immigrants, and memory-based immigrants, are integrated into ACO algorithms for solving DOPs. From this framework, three ACO algorithms, where immigrant ants are generated using the aforementioned immigrants schemes and replace existing ants in the current population, are proposed and investigated. Moreover, two novel types of dynamic travelling salesman problems (DTSPs) with traffic factors, i.e., under random and cyclic dynamic environments, are proposed for the experimental study. The experimental results based on different DTSP test cases show that each proposed algorithm performs well on different environmental cases and that the proposed algorithms outperform several other peer ACO algorithms.     

Quantized H∞ Control for Networked Systems with Communication Constraints

The problem of quantized H_∞ control for networked control systems (NCSs) subject to time‐varying delay and multiple packet dropouts is investigated in this paper. Both the control input and the measurement output signals are quantized before being transmitted and the quantized errors are described as sector bound uncertainties. The measurement channel and the control channel packet dropouts are considered simultaneously, and the stochastic variables satisfying Bernoulli random binary distribution are utilized to model the random multiple packet dropouts. Sufficient conditions for the existence of an observer‐based controller are established to ensure the exponential mean‐square stablility of the closed‐loop system and achieve the optimal H_∞ disturbance attenuation level. By using a globally convergent algorithm involving convex optimization, the nonconvex feasibility can be solved successfully. Finally, a numerical example is given to illustrate the effectiveness and applicability of the proposed method.     

Fault tolerant authenticated quantum direct communication immune to collective noises

This study proposes two new coding functions for GHZ states and GHZ-like states, respectively. Based on these coding functions, two fault tolerant authenticated quantum direct communication (AQDC) protocols are proposed. Each of which is robust under one kind of collective noises: collective-dephasing noise and collective-rotation noise, respectively. Moreover, the proposed AQDC protocols enable a sender to send a secure as well as authenticated message to a receiver within only one step quantum transmission without using the classical channels.     

Novel image encryption/decryption based on quantum Fourier transform and double phase encoding

A novel gray-level image encryption/decryption scheme is proposed, which is based on quantum Fourier transform and double random-phase encoding technique. The biggest contribution of our work lies in that it is the first time that the double random-phase encoding technique is generalized to quantum scenarios. As the encryption keys, two phase coding operations are applied in the quantum image spatial domain and the Fourier transform domain respectively. Only applying the correct keys, the original image can be retrieved successfully. Because all operations in quantum computation must be invertible, decryption is the inverse of the encryption process. A detailed theoretical analysis is given to clarify its robustness, computational complexity and advantages over its classical counterparts. It paves the way for introducing more optical information processing techniques into quantum scenarios.     

Quantum dialogue protocols immune to collective noise

This work proposes two quantum dialogue protocols, each of which is robust against one of the following two kinds of collective noise: collective-dephasing noise and collective-rotation noise. Both quantum dialogue protocols are constructed from four-qubit DF states that consist of two Bell states. The receiver simply performs two Bell state measurements to obtain the secret message. Moreover, the proposed protocols are free from information leakage because some shared private quantum states are established in the new protocols to allow the legitimate users to exchange their secret messages securely.     

Sliding-mode observers for nonlinear systems with unknown inputs and measurement noise

This paper deals with the design of observers for Lipschitz nonlinear systems with not only unknown inputs but also measurement noise when the observer matching condition is not satisfied. First, an augmented vector is introduced to construct an augmented system, and an auxiliary output vector is constructed such that the observer matching condition is satisfied and then a high-gain sliding mode observer is considered to get the exact estimates of both the auxiliary outputs and their derivatives in a finite time. Second, for nonlinear system with both unknown inputs and measurement noise, an adaptive robust sliding mode observer is developed to asymptotically estimate the system’s states, and then an unknown input and measurement noise reconstruction method is proposed. Finally, a numerical simulation example is given to illustrate the effectiveness of the proposed methods.     

Spindle-shaped microfluidic chamber with uniform perfusion flows

The reaction chamber is important due to its wide applications. Based on the idea of the bionics, a novel spindle-shaped chamber (S-chamber) for microfluidics was designed to provide uniform flow and eliminate stagnant corners for microchannels. The computational fluid dynamics simulation results demonstrate that these S-chambers have a better performance compared to the conventional diamond-shaped chambers. An S-chamber with the optimized shape, which consists of a rectangle reaction region interfaced to the inlet/outlet channel through an expansion region with smooth arc edges, was fabricated by micromolding of polydimethylsiloxane. This S-chamber was fixed into a microreactor and mounted horizontally on a synthesizer for biochemical reactions. Solvent perfusion experiments and synthetic optimization experiments for in situ synthesis of peptide nucleic acids microarray were performed. The experimental results indicate that the newly designed and fabricated S-chamber provides excellent homogeneous perfusion flows. This type of S-chamber is designed for the most convenient fixation in the horizontal direction, without the need to consider the complicated effect caused by other housing directions. It has a wide application for cell culturing, microarray synthesis, gene hybridization, and many other microfluidic system-based techniques requiring uniform flow conditions.     

Probability hypothesis density filter based on strong tracking MIE for multiple maneuvering target tracking

Taking into account the difficulties of multiple maneuvering target tracking due to the unknown target number and the uncertain acceleration, a novel multiple maneuvering target tracking algorithm based on the Probability Hypothesis Density (PHD) filter and Modified Input Estimation (MIE) technique is proposed in this paper. First, the unknown acceleration vector is added to the target state to form a new augmented state vector. Then, strong tracking filter multiple fading factors are introduced to the MIE method which can adjust the prediction covariance and the corresponding filter gain at different rates in real time, so that the MIE method can adaptively track high maneuvering targets well. Finally, we combine this adaptive MIE method with the PHD filter, which can effectively track multiple maneuvering targets without much prior information. Simulation results show that the proposed algorithm has a higher tracking precision and a better real-time performance than the conventional maneuvering target tracking algorithms.