DeepAI AI Chat
Log In Sign Up

Bi-objective Search with Bi-directional A*

by   Saman Ahmadi, et al.

Bi-objective search is a well-known algorithmic problem, concerned with finding a set of optimal solutions in a two-dimensional domain. This problem has a wide variety of applications such as planning in transport systems or optimal control in energy systems. Recently, bi-objective A*-based search (BOA*) has shown state-of-the-art performance in large networks. This paper develops a bi-directional variant of BOA*, enriched with several speed-up heuristics. Our experimental results on 1,000 benchmark cases show that our bi-directional A* algorithm for bi-objective search (BOBA*) can optimally solve all of the benchmark cases within the time limit, outperforming the state of the art BOA*, bi-objective Dijkstra and bi-directional bi-objective Dijkstra by an average runtime improvement of a factor of five over all of the benchmark instances.


page 1

page 2

page 3

page 4


On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation

We propose to train bi-directional neural network language model(NNLM) w...

Towards Real-time Mispronunciation Detection in Kids' Speech

Modern mispronunciation detection and diagnosis systems have seen signif...

Bi-Directional Grid Constrained Stochastic Processes' Link to Multi-Skew Brownian Motion

Bi-Directional Grid Constrained (BGC) stochastic processes (BGCSPs) cons...

The bi-objective multimodal car-sharing problem

The aim of the bi-objective multimodal car-sharing problem (BiO-MMCP) is...

A Pareto-metaheuristic for a bi-objective winner determination problem in a combinatorial reverse auction

The bi-objective winner determination problem (2WDP-SC) of a combinatori...