A combination of genetic algorithm and particle swarm optimization (PSO) for vehicle routing problems with time windows (VRPTW) is proposed in this paper. The improvements of the proposed algorithm include: using the particle real number encoding method to decode the route to alleviate the computation burden, applying a linear decreasing function based on the number of the iterations to provide balance between global and local exploration abilities, and integrating with the crossover operator of genetic algorithm to avoid the premature convergence and the local minimum. The experimental results show that the proposed algorithm is not only more efficient and competitive with other published results but can also obtain more optimal solutions for solving the VRPTW issue. One new well-known solution for this benchmark problem is also outlined in the following.

In this paper, Fourier transform profilometry (FTP) using a colour fringe selection technique for accurate phase map reconstruction is newly proposed to overcome the limitation of FTP in measuring objects having arbitrary surface colours. The sinusoidal colour fringe pattern is encoded to form a unique colour pattern for projecting onto the object’s surface, and its reflected deformed fringe image is taken using a triple-colour CCD camera and rapidly processed by the developed FTP method employing a novel band-pass filter. A new 3D vision system is capable of measuring objects with a high speed of up to 60  frames s − 1. To reconstruct the 3D profile of an object having arbitrary surface colours, an innovative strategy is developed to identify the colour channel of the detected fringe pattern with the best modulation transfer function (MTF) for retrieving accurate phase maps. The experimental results demonstrate that the system has the capability to acquire 3D maps at a high speed while the measurement accuracy of the developed method is substantially better than that of the traditional FTP method. By measuring the standard step heights in a repeatability test, it is confirmed that a maximum measured error can be controlled to less than 2.8% of the overall measuring depth range.