The Closed-Loop Layout Problem (CLLP) is an NP-hard mixed optimization problem, in which an optimal placement order of facilities is found along adjustable rectangle loop with the objection of minimizing the total transport cost of material flow between facilities. In most of the existing methods, meta-heuristic algorithm was used to find the optimal order for the placement of facilities, and enumeration method was applied to find the optimal size of the rectangle loop, which causes extremely low efficiency. To solve this problem, a Hybrid Population-Based Incremental Learning (HPBIL) algorithm was proposed for solving CLLP. In the algorithm, the Discrete Population-Based Incremental Learning (DPBIL) operator and Continuous PBIL (CPBIL) operator were used separately to search the optimal placement order of facilities and the size of rectangle loop at the same time, which improved the efficiency of search. Furthermore, a local search algorithm was designed to optimize some good solutions in each iteration, enhancing the refinement ability. Simulation experiments were carried out on 13 CLLP instances. The results show that HPBIL algorithm finds the best new optimal layouts on 9 instances, and is significantly superior to the algorithms to be compared on the optimization ability for CLLP.

When solving the optimal solutions of 0-1 Knapsack Problems (KPs), the traditional Genetic Algorithm (GA) has insufficient local refinement ability and the simple local search algorithm has limited global exploration ability. Aiming at these problems, two algorithms were integrated to the Hybrid Greedy Genetic Algorithm (HGGA). Under the GA global search framework, local search module was added, and the traditional repair operator based only on item value density was improved, the greedy hybrid option based on item value was added, so as to accelerate the optimization process. In HGGA, the population was led to carry out fine search in the excellent solution space of evolution, and the classical operators of GA were relied on to expand the global search space, so as to achieve a good balance between the refinement ability and the development ability of the algorithm. HGGA was tested on three sets of data. The results show that in the first set of 15 test cases, HGGA is able to find the optimal solution on 12 cases, with a success rate of 80%; on the second small-scale dataset, the performance of HGGA is obviously better than those of other similar GA and other meta-heuristic algorithms; on the third large-scale dataset, HGGA is more stable and efficient than other meta-heuristic algorithms.

Video monitoring has been applied to various occasions to provide efficient information for safe guarding. In this paper, the coverage problems in Visual Sensor Network (VSN) were surveyed. VSN has the characteristics as directional sensor network. However, if take the facing direction of monitoring target into account, VSN is different from the ordinary directional sensor network. According to whether considering the facing direction of monitoring target in the sensor model, the works on coverage of VSN including target coverage, area coverage and barrier coverage were introduced in this paper respectively. Finally, the current problems and future research direction were discussed.

Regarding the disadvantages of uneven clustering and fixed round time in Low Energy Adaptive Clustering Hierarchy (LEACH) protocol, the Dynamic Round-Time (DRT) algorithm based on LEACH (LEACH-DRT) was proposed to prolong network life time. The algorithm obtained clusters' and member nodes' information from base station, and then figured out clusters' round time according to the number of clusters' member nodes and clusters' remaining energy. The time information was sent to different clusters by base station. Clusters began to work according to the time information received. Meanwhile, by using the new cluster head election mechanism, it avoided the data loss and useless energy consumption caused by the cluster's insufficient energy. The analysis and simulation results show that the improved algorithm prolongs about four times network life time and reduces the probability of data loss by 18% than LEACH protocol. It also demonstrates that LEACH-DRT algorithm achieves a better application effect at balancing energy consumption and data loss rate.

Taking full consideration of that CMOS multi-core embedded processor only provides global Dynamic Voltage Scaling (DVS) and its power leakage is serious, this paper proposed a new power-aware scheduling algorithm GRR&CS for hard real-time tasks in multi-core embedded environment. The power saving was achieved by three steps, including greedy-based static tasks partition, global resource reclamation based dynamic load balance and dynamic core scaling. The algorithm also keeps the schedulability of tasks. The experimental results show that the proposed algorithm saves more about 14.8%-41.2% energy than other existing works.

In order to solve the preferable selection problem of offensive mine-laying plans for unmanned aerial vehicles, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based on connection number was adopted. With reference to the traditional essential factors for evaluation of mine-laying plans, the synthesized parameter of Unmanned Aerial Vehicle (UAV) was also selected as the main index to scale the effect of mine-laying platform. Then the connection number was used to describe the identity-contrary degree based on integrated plan, while the information entropy weight of each factor was calculated. For the reliability of the ranking process, the relative certainty probability power was improved with the stabilization coefficient, which could be used to evaluate and rank the mine-laying plans. The simulation results indicate the availability of this algorithm.

To improve the data storage performance and utility efficiency of 3D model on military simulation entities, categories of the models were proposed. Rules of 3D models on level of details, grade of damage, texture and grouping were constituted. Data storage framework for 3D model, hierarchical architecture of the models, and data structures for each level architecture were constructed. Finally, the algorithm for reconstructing 3D models was introduced.

Three new technologies ware introduced by the authors in the past year,i.e.:(a) TranGene technique.By injection gene segment,it guides the evolution direction,controls knowledge discover process.(b) Overlapped gene expression.It borrows the idea of overlap gene expression from biological study,introduces overlapped gene expression,and saves space for gene expression.(c) Backtracking evolution.It comes from atavism in biology and proposes the concept of backtracking GEP algorithms,designing geometric proportion increased checkpoint sequence and accelerated increased checkpoint sequence to restrict the backtracking process. Experiments show that all three techniques respectively boost the performance of GEP by one or two magnitudes.

Along with the functions of real-time embedded systems becoming more and more complex, and the market press becoming pricking up, the design of real-time embedded systems needs modern software engineering methodologies. Rather recently, using UML in real time domains becomes a hot topic. Real-time embedded systems usually are compositions of event-driven discrete systems and dataflow-based continuous systems. But the extensions of UML for real-time domains (UML-RT) only support event-driven systems modeling. This paper first analysed the advantages and problems of using UML in real time systems design. Second, it discussed UML-RT based real-time embedded systems design methodology and proposed an extension of UML-RT to support Dataflow modeling. Finally, this paper presented an automobile cruise control system as an example to illuminate this methodology.