Multimodal Transportation Network Design Using Physarum Polycephalum-Inspired Multi-agent Computation Methods

2018 ◽  
pp. 105-116 ◽  
Author(s):  
Rishi Vanukuru ◽  
Nagendra R. Velaga
Keyword(s):  
Network Design ◽  
Physarum Polycephalum ◽  
Transportation Network ◽  
Multimodal Transportation ◽  
Multi Agent

scholarly journals Mechanisms Inducing Parallel Computation in a Model of Physarum polycephalum Transport Networks

2015 ◽  
Vol 25 (01) ◽  
pp. 1540004 ◽  
Author(s):  
Jeff Jones
Keyword(s):  
Physarum Polycephalum ◽  
Network Formation ◽  
Proximity Graphs ◽  
Complex Adaptive ◽  
Division Problems ◽  
Scaling Parameters ◽  
Angle Rotation ◽  
Multi Agent ◽  
Robotic Devices ◽  
Adaptive Behaviours

The giant amoeboid organism true slime mould Physarum polycephalum dynamically adapts its body plan in response to changing environmental conditions and its protoplasmic transport network is used to distribute nutrients within the organism. These networks are efficient in terms of network length and network resilience and are parallel approximations of a range of proximity graphs and plane division problems. The complex parallel distributed computation exhibited by this simple organism has since served as an inspiration for intensive research into distributed computing and robotics within the last decade. P. polycephalum may be considered as a spatially represented parallel unconventional computing substrate, but how can this ‘computer’ be programmed? In this paper we examine and catalogue individual low-level mechanisms which may be used to induce network formation and adaptation in a multi-agent model of P. polycephalum. These mechanisms include those intrinsic to the model (particle sensor angle, rotation angle, and scaling parameters) and those mediated by the environment (stimulus location, distance, angle, concentration, engulfment and consumption of nutrients, and the presence of simulated light irradiation, repellents and obstacles). The mechanisms induce a concurrent integration of chemoattractant and chemorepellent gradients diffusing within the 2D lattice upon which the agent population resides, stimulating growth, movement, morphological adaptation and network minimisation. Chemoattractant gradients, and their modulation by the engulfment and consumption of nutrients by the model population, represent an efficient outsourcing of spatial computation. The mechanisms may prove useful in understanding the search strategies and adaptation of distributed organisms within their environment, in understanding the minimal requirements for complex adaptive behaviours, and in developing methods of spatially programming parallel unconventional computers and robotic devices.

scholarly journals A Multi-Agent-Based Intelligent Sensor and Actuator Network Design for Smart House and Home Automation

2013 ◽  
Vol 2 (3) ◽  
pp. 557-588 ◽  
Author(s):  
Qingquan Sun ◽  
Weihong Yu ◽  
Nikolai Kochurov ◽  
Qi Hao ◽  
Fei Hu
Keyword(s):  
Network Design ◽  
Home Automation ◽  
Intelligent Sensor ◽  
Agent Based ◽  
Multi Agent ◽  
Smart House

scholarly journals Modeling the Multicommodity Multimodal Routing Problem with Schedule-Based Services and Carbon Dioxide Emission Costs

2015 ◽  
Vol 2015 ◽  
pp. 1-21 ◽  
Author(s):  
Yan Sun ◽  
Maoxiang Lang
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Transportation Network ◽  
Linearization Method ◽  
Mixed Integer ◽  
Multicommodity Flow ◽  
Routing Problem ◽  
Multimodal Transportation ◽  
Proposed Model ◽  
Freight Routing

We explore a freight routing problem wherein the aim is to assign optimal routes to move commodities through a multimodal transportation network. This problem belongs to the operational level of service network planning. The following formulation characteristics will be comprehensively considered: (1) multicommodity flow routing; (2) a capacitated multimodal transportation network with schedule-based rail services and time-flexible road services; (3) carbon dioxide emissions consideration; and (4) a generalized costs optimum oriented to customer demands. The specific planning of freight routing is thus defined as a capacitated time-sensitive multicommodity multimodal generalized shortest path problem. To solve this problem systematically, we first establish a node-arc-based mixed integer nonlinear programming model that combines the above formulation characteristics in a comprehensive manner. Then, we develop a linearization method to transform the proposed model into a linear one. Finally, a computational experiment from the Chinese inland container export business is presented to demonstrate the feasibility of the model and linearization method. The computational results indicate that implementing the proposed model and linearization method in the mathematical programming software Lingo can effectively solve the large-scale practical multicommodity multimodal transportation routing problem.

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