All-Optical Implementation of the Ant Colony Optimization Algorithm

A multi-center joint distribution optimization model considering carbon emissions and customer satisfaction

Logistics enterprises are searching for a sustainable solution between the economy and the environment under the concept of green logistics development. Given that, this study integrates carbon emission as one of the costs into the vehicle routing problem with time window (VRPTW) and establishes a multi-center joint distribution optimization model taking into account distribution cost, carbon emission, and customer satisfaction. In the study of carbon emissions, this paper selected the vehicle load rate and vehicle distance as the main indicators. An improved ant colony algorithm is designed to solve the model by introducing the elite strategy, the saving strategy, vehicle service rules, and customer selection rules. Simulation results show that compared with the traditional ant colony optimization and genetic algorithm, the improved ant colony algorithm can effectively reduce the distribution cost and carbon emission and, improve customer satisfaction.

Artificial intelligence for photonics and photonic materials

Artificial intelligence (AI) is the most important new methodology in scientific research since the adoption of quantum mechanics and it is providing exciting results in numerous fields of science and technology. In this review we summarize research and discuss future opportunities for AI in the domains of photonics, nanophotonics, plasmonics and photonic materials discovery, including metamaterials.

On-chip photonic decision maker using spontaneous mode switching in a ring laser

Efficient and accurate decision making is gaining increased importance with the rapid expansion of information communication technologies including artificial intelligence. Here, we propose and experimentally demonstrate an on-chip, integrated photonic decision maker based on a ring laser. The ring laser exhibits spontaneous switching between clockwise and counter-clockwise oscillatory dynamics; we utilize such nature to solve a multi-armed bandit problem. The spontaneous switching dynamics provides efficient exploration to find the accurate decision. On-line decision making is experimentally demonstrated including autonomous adaptation to an uncertain environment. This study paves the way for directly utilizing the fluctuating physics inherent in ring lasers, or integrated photonics technologies in general, for achieving or accelerating intelligent functionality.

All-Optical Reinforcement Learning In Solitonic X-Junctions

Ethology has shown that animal groups or colonies can perform complex calculation distributing simple decision-making processes to the group members. For example ant colonies can optimize the trajectories towards the food by performing both a reinforcement (or a cancellation) of the pheromone traces and a switch from one path to another with stronger pheromone. Such ant’s processes can be implemented in a photonic hardware to reproduce stigmergic signal processing. We present innovative, completely integrated X-junctions realized using solitonic waveguides which can provide both ant’s decision-making processes. The proposed X-junctions can switch from symmetric (50/50) to asymmetric behaviors (80/20) using optical feedbacks, vanishing unused output channels or reinforcing the used ones.

Optical NP problem solver on laser-written waveguide platform

Cognitive photonic networks are researched to efficiently solve computationally hard problems. Flexible fabrication techniques for the implementation of such networks into compact and scalable chips are desirable for the study of new optical computing schemes and algorithm optimization. Here we demonstrate a femtosecond laser-written optical oracle based on cascaded directional couplers in glass, for the solution of the Hamiltonian path problem. By interrogating the integrated photonic chip with ultrashort laser pulses, we were able to distinguish the different paths traveled by light pulses, and thus infer the existence or the absence of the Hamiltonian path in the network by using an optical correlator. This work proves that graph theory problems may be easily implemented in integrated photonic networks, down scaling the net size and speeding up execution times.