Similar Trajectory Search with Spatio-Temporal Deep Representation Learning

Similar trajectory search is a crucial task that facilitates many downstream spatial data analytic applications. Despite its importance, many of the current literature focus solely on the trajectory’s spatial similarity while neglecting the temporal information. Additionally, the few papers that use both the spatial and temporal features based their approach on a traditional point-to-point comparison. These methods model the importance of the spatial and temporal aspect of the data with only a single, pre-defined balancing factor for all trajectories, even though the relative spatial and temporal balance can change from trajectory to trajectory. In this article, we propose the first spatio-temporal, deep-representation-learning-based approach to similar trajectory search. Experiments show that utilizing both features offers significant improvements over existing point-to-point comparison and deep-representation-learning approach. We also show that our deep neural network approach is faster and performs more consistently compared to the point-to-point comparison approaches.

On the Benefits of Populations for the Exploitation Speed of Standard Steady-State Genetic Algorithms

It is generally accepted that populations are useful for the global exploration of multi-modal optimisation problems. Indeed, several theoretical results are available showing such advantages over single-trajectory search heuristics. In this paper we provide evidence that evolving populations via crossover and mutation may also benefit the optimisation time for hillclimbing unimodal functions. In particular, we prove bounds on the expected runtime of the standard ($$\mu +1$$ μ + 1 ) GA for OneMax that are lower than its unary black box complexity and decrease in the leading constant with the population size up to $$\mu =o\left( \sqrt{\log n}\right) $$ μ = o log n . Our analysis suggests that the optimal mutation strategy is to flip two bits most of the time. To achieve the results we provide two interesting contributions to the theory of randomised search heuristics: (1) A novel application of drift analysis which compares absorption times of different Markov chains without defining an explicit potential function. (2) The inversion of fundamental matrices to calculate the absorption times of the Markov chains. The latter strategy was previously proposed in the literature but to the best of our knowledge this is the first time is has been used to show non-trivial bounds on expected runtimes.

A heuristic for the minimum cost chromatic partition problem

The graph coloring problem consists in coloring the vertices of a graph G=(V, E) with a minimum number of colors, such as that any two adjacent vertices receive different colors. The minimum cost chromatic partition problem (MCCPP) is an extension of the graph coloring problem in which there are costs associated with the colors and one seeks a vertex coloring minimizing the sum of the costs of the colors used in each vertex. The problem finds applications in VLSI design and in some scheduling problems modeled on interval graphs. We propose a trajectory search heuristic using local search, path-relinking, and perturbations for solving MCCPP and discuss computational results.

Method for optimal conflict-free aircraft trajectory generation

Purpose A number of automated tools will be required for the purpose of enabling efficient services in air traffic control. The purpose of this paper is to devise an optimal flight trajectory search method that optimizes airspace system efficiency for 3D space in the presence of uncertainties. Design/methodology/approach This paper put forward an optimization model for generating applicable solutions of multi-aircraft conflict resolution problem, and the solution is based on the principle of optimality. Findings The conflict resolution problem between multiple aircraft can be described by spatial discretization, and the approach taken digitizes the 3D space into a grid of nodes. Practical implications The simulation examples are given to illustrate the validity of trajectory search model and stress on the impact of different system parameters. Originality/value Realistic constraints that are convenient to operate are incorporated in the system model, and the results show that it can provide reliable decision-making for conflict avoidance.