No abstract

Increasingly, tourists are planning trips by themselves using the vast amount of information available on the Web. However, they still expect and want trip plan advisory services. In this paper, we study the tour planning problem in which our goal is to design a tour trip with the most desirable sites, subject to various budget and time constraints. We first establish a framework for this problem, and then formulate it as a mixed integer linear programming problem. However, except when the size of the problem is small, say, with less than 20-30 sites, it is computationally infeasible to solve the mixed-integer linear programming problem. Therefore, we propose a heuristic method based on local search ideas. The method is efficient and provides good approximation solutions. Numerical results are provided to validate the method. We also apply our method to the team orienteering problem, a special case of the tour planning problem which has been considered in the literature, and compare our method with other existing methods. Our numerical results show that our method produces very good approximation solutions with relatively small computational efforts comparing with other existing methods.

Rescue robots can replace rescue workers in search and rescue missions in unknown environments and hence play an important role in disaster relief. To realize the advantages of high carrying capacity, easy control, and simple structure to adapt to a complex disaster scene, a novel wheel-legged rescue robot, integrated with rescue function modules, was designed for the present work. Three motion states were analyzed in detail. Mechanical properties were studied to provide basis for parameter optimization. The performance indices, which include mechanical properties, motion amplitudes and movement stability, were proposed, and the structural parameters were further analyzed and optimized based on these performance indices to make the overall performance of the robot achieve the best. Results show that the motion state of the wheel-legged rescue robot can perform real-time transformations and hence can be used in complex environments.

A wheel-legged rescue robot design with strong environmental adaptability is proposed. The design presented is aimed at helping rescue workers complete their missions, such as environmental and personnel search, quickly and accurately. So it has broad application prospects. In order to achieve the advantages of simple structure, easy control, small occupation space, and wide motion range, a wheel-legged rescue robot is designed in this paper, and the robot can realize three kinds of motion states, which include wheel state, rotation center lifting process, and leg state. Then the motion states are analyzed in detail, which provides a reference for motion control. Considering the wheel state and leg state share the same structure to contact with the ground, the effect of the stiffness of wheel-legged structure to the motion performance is analyzed. Then the experiment is carried out to prove the feasibility of the structure design. This study offers a design and quantitative analysis for wheel-legged rescue robot. Furthermore, a basis for future control research and engineering applications is established.

Most inventory models in the literature assume that demands are independent among different time periods. However, a number of recent studies suggest that demands are often correlated over different time periods, which motivates our work here. In this paper, we study a class of periodic review (s, S) inventory systems in which demands are correlated and modeled as a Markov-modulated process. Using a Maclaurin series analysis and a Pade approximation, as well as an infinite system of linear equations, we develop algorithms to calculate the moments of the inventory level based on which various performance measures of the system can also be evaluated. Numerical experiments show that our approach is quite efficient and provides accurate estimates for the moments of the inventory level and other related performance measures.