The Capacitated Traveling Salesman Problem with Pickups and Deliveries on a Tree
The Capacitated Traveling Salesman Problem with Pickups and Deliveries (CTSP-PD)[1] can be defined on an undirected graph T=(V,E), where V is a set of n vertices and E is a set of edges. A nonnegative weight d(e) is associated with each edge e∈ E to indicate its length. Each vertex is either a pickup point, a delivery point, or a transient point. At each pickup point is a load of unit size that can be shipped to any delivery point which requests a load of unit size. Hence we can use a(v)=1,0,–1 to indicate v to be a pickup, a transient, or a delivery point, and a(v) is referred to as the volume of v. The total volumes for pickups and for deliveries are usually assumed to be balanced, i.e., $\sum_{v\in {\it V}}{\it a}({\it v})=0$, which implies that all loads in pickup points must be shipped to delivery points . Among V, one particular vertex r ∈ V is designated as a depot, at which a vehicle of limited capacity of k ≥ 1 starts and ends. The problem aims to determine a minimum length feasible route that picks up and delivers all loads without violating the vehicle capacity.

title: A Compromised Large-Scale Neighborhood Search Heuristic for Cargo Loading Planning
abstract: In this work, we propose a compromised large-scale neighborhood, which is embedded in simulated annealing to solve a cargo loading planning problem arising in logistics industry. It is "compromised" because it makes a tradeoff between the extensive backward checking work incurred in traditional subset-disjoint restriction and the possible infeasibility resulting from the relaxing the restriction. Extensive experiments have shown the competitive advantages of the heuristic approach. The proposed neighborhood search method is generally applicable.

title: A compromised large-scale neighborhood search heuristic for capacitated air cargo loading planning
abstract: Cost effectiveness is central to the air freight forwarders. In this work, we study how an air freight forwarder should plan its cargo loading in order to minimize the total freight cost given a limited number of rented containers. To solve the problem efficiently for practical implementation, we propose a new large-scale neighborhood search heuristic. The proposed large-scale neighborhood relaxes the subset-disjoint restriction made in the existing literature; the relaxation risks a possibility of infeasible exchanges while at the same time it avoids the potentially large amount of checking effort required to enforce the subset-disjoint restriction. An efficient procedure is then used to search for improvement in the neighborhood. We have also proposed a subproblem to address the difficulties caused by the fixed charges. The compromised large-scale neighborhood (CLSN) search heuristic has shown stably superior performance when compared with the traditional large-scale neighborhood search and the mixed integer programming model.

title: k-Center Problems with Minimum Coverage
abstract: The k-center problem is a well-known facility location problem and can be described as follows: Given a complete undirected graph G=(V,E), a metric d:V×V→ℝ + and a positive integer k, we seek a subset U ⊆ V of at most k centers which minimizes the maximum distances from points in V to U. Formally, the objective function is given by: 
 
$$ \textstyle\min_{U\subseteq V,|U|\leq k}\max_{v\in V}\min_{r\in U}d(v,r).$$ 
 
As a typical example, we may want to set up k service centers (e.g., police stations, fire stations, hospitals, polling centers) and minimize the maximum distances between each client and these centers. The problem is known to be \(\mathcal{NP}\)-hard .

title: Meta-heuristic Algorithm for the Transshipment Problem with Fixed Transportation Schedules
abstract: In this work, we develop an efficient meta-heuristic genetic algorithm for a different type of transshipment problem with supplier and customer time windows, where flow through the crossdock (a kind of transshipment center) is constrained by fixed transportation schedules and crossdocks capacities, and which was proved to be NP -complete in the strong sense. And computational experiments are conducted to show the proposed heuristic outperforms CPLEX.

title: A stochastic beam search for the berth allocation problem
abstract: In this paper, the optimization of the Berth Allocation Problem (BAP) is transformed into a multiple stage decision making procedure and a new multiple stage search method, namely stochastic beam search algorithm, is proposed to solve it. New techniques such as an improved beam search scheme, a two-phase node goodness estimation, and a stochastic node selection criteria are proposed. Real-life information provided by Singapore Port was collected as our test data. Experimental results show that the proposed stochastic beam search is more accurate and efficient than both the state-of-the-art meta-heuristic and the traditional determinist beam search.

title: Personality Based Latent Friendship Mining
abstract: Methods and apparatus for detecting imperfections in adhesive coatings formed on fingers of beams are disclosed. The present invention relates, in one aspect, to a method for preparing a first work piece for joining with a second work piece. The method involves forming a finger in the first work piece, then applying an adhesive coating on the finger. A determination is made to determine whether the adhesive coating is defective through the used of a sensing mechanism which is arranged to scan across a portion of the finger. In one embodiment, a defect in the adhesive coating on the finger is defined as a void.

title: Remote Video Monitoring Over the WWW
abstract: Remote video monitoring has become increasingly important for monitoring the security of destined locations. Traditional security monitoring systems using coaxial cables and VCR recording systems are expensive and ineffective. With the rapid growth of the Internet, it is now possible to use it as an intermediate transmission medium to support real-time video transmission. This paper proposes a web-based remote monitoring system known as iSecure. Apart from the essential live or stored video transmission, intelligent monitoring and web-based monitoring are also supported. As the transmission of live video data through the packet switched network environment of the Internet can result in packet loss and quality degradation, the iSecure system has implemented an adaptive transmission and recovery mechanism to enhance the quality of real-time video transmission. Intelligent monitoring for elevator security and face-based door access control applications has been incorporated. The iSecure system can be used as a framework for developing other intelligent remote monitoring applications.

title: Exploiting Parallelism to Accelerate Keyword Search on Deep-Web Sources
abstract: Increasingly, biological data is being shared over the deep web. Many biological queries can only be answered by successively searching a number of distinct web-sites. This paper introduces a system that exploits parallelization for accelerating search over multiple deep web data sources. An interactive, two-stage multi-threading system is developed to achieve task parallelization, thread parallelization, and pipelined parallelization. We show the effectiveness of our system by considering a number of queries involving SNP datasets. We show that most of the queries can be accelerated significantly by exploiting these three forms of parallelism.

title: Inequivalent manifold ranking for content-based image retrieval
abstract: We propose to improve the effectiveness and scalability of graph based manifold ranking methods in image retrieval applications by emphasizing reliable images while damping the effect of noisy or irregular ones. Label information is firstly passed between most reliable data points, then propagated to less reliable ones on manifold structure. By treating these images inequivalently, undesirable effect of noisy samples is greatly reduced, thus effectiveness of manifold ranking algorithms is enhanced. Also, graph size in terms of number of nodes and edges is dramatically reduced, resulting in a great speed-up of the algorithm. Our experiment on real world image data set demonstrates the effectiveness of the proposed approach.

title: Analysis on Network Model Parameters of BP Neural Network in the Assessment for Bridge Reliability