This paper investigates a new collision-free routing problem of a multi-robot system. The objective is to minimize the cycle time of operation tasks for each robot while avoiding collisions. The focus is set on the operation of the end effector and its connected joint, and the operation is projected onto a circular area on the plane. We propose to employ a time-space network (TSN) model that maps the robot location constraints into the route planning framework, leading to a mixed integer programming (MIP) problem. A dedicated genetic algorithm is proposed for solving this MIP problem and a new encoding scheme is designed to fit the TSN formulation. Simulation experiments indicate that the proposed model can obtain the collision-free route of the considered multi-robot system. Simulation results also show that the proposed genetic algorithm can provide fast and high-quality solutions, compared to two state-of-the-art commercial solvers and a practical approach.

Energy consumption is expected to be reduced while maintaining high productivity for container handling. This paper investigates a new energy-efficient scheduling problem of automated container terminals, in which quay cranes (QCs) and lift automated guided vehicles (AGVs) cooperate to handle inbound and outbound containers. In our scheduling problem, operation times and task sequences are both to be determined. The underlying optimization problem is mixed-integer nonlinear programming (MINLP). To deal with its computational intractability, a customized and efficient genetic algorithm (GA) is developed to solve the studied MINLP problem, and lexicographic and weighted-sum strategies are further considered. An -constraint algorithm is also developed to analyze the Pareto frontiers. Comprehensive experiments are tested on a container handling benchmark system, and the results show the effectiveness of the proposed lexicographic GA, compared to results obtained with two commonly-used metaheuristics, a commercial MINLP solver, and two state-of-the-art methods.

The impact of human body heat dissipation on the containment of a fume hood was conducted via experiments and numerical model. The experiments evaluated hood face velocity and the temperature around the mannequin; the results validated the simulation. The numerical model was based on the governing equations of fluid flow via the finite volume method. The face velocities (0.3–0.9 m·s− 1 ) and temperature differences (11°C, 8°C and 5°C) between the surface of the mannequin and its surroundings were used as variables. The numerical results show that in addition to the blockage effect of the worker standing in front of the fume hood, there is a more important thermal effect on the containment of fume hood. The thermal plume carries pollutants leaking out of the hood face to the breathing zone. The face velocity and dimensionless value (Gr/Re 2 ) are recommended to be 0.4–0.6 m·s− 1 and 20–35 respectively, to reduce the influence of human thermal plume on the containment of fume hood and energy waste. The formula related to the rising distance of thermal plume, Grashof and Reynolds numbers (Gr/Re 2 ) was determined.

The refrigerated/chilled quality of marine cargo is vitally influenced by the temperature distribution inside reefer container. The stacking mode is a key factor affecting temperature distribution. CFD method is employed to model and simulate a 20-ft standard reefer container, in which seven cargo stacking modes are emulated to numerically analyze the internal temperature distribution inside the container. The stacking cargo is assumed as solid stack without heat release and the variables, such as stack number, height, length and gap, are considered in seven simulation cases. The results show that the temperature distributions become disordered along with increase in the stack height; the temperature difference increase along with increase in the stack length; the temperature tends to be isothermal when the gap of the stacks or the space between the stack and sidewall surface is enlarging. The simulation results are in very good agreement with the experimental results.

In this paper, we study the collision-free routing of a multi-robot system to complete given tasks in the shortest time. In a robotic assembly unit, several stations work serially and in parallel. In a station, multiple robots share the same workspace and face the challenge of minimizing the cycle time and avoiding collisions at the same time. For this problem, we propose a new mathematical model that is the so-called timespace network (TSN) model. The TSN model can map the robot location constraints into the routing planning framework, leading a mixed integer programming problem. By solving this mixed integer programming problem, the collision-free path of multiple robots can be obtained. Finally, The simulation results illustrate the proposed TSN model can obtain the collision-free route of the multi-robot system.