A Receding Horizon Genetic Algorithm for Dynamic Resource Allocation: A Case Study on Optimal Positioning of Tugs
نویسنده
چکیده
This paper presents a receding horizon genetic algorithm (RHGA) for dynamic resource allocation. The algorithm combines methods from control theory and computational intelligence to simultaneously solve the problems of (i) coordinated control of resources, (ii) task assignment, and (iii) multiple target tracking in a dynamic environment. A simulated case study on optimal positioning of a fleet of tugs along the northern Norwegian coast serves as a means of evaluating the algorithm. In terms of reducing the risk of oil tanker drifting accidents, the study shows that the RHGA is able to iteratively plan movement trajectories for each individual tug such that the net collective behaviour of the tugs outperforms that of stand-by tugs stationed at bases located uniformly along the coast. The promising results suggest great potential for further development and generalisation to other dynamic resource allocation problems.
منابع مشابه
A Receding Horizon Genetic Algorithm for Dynamic Multi-target Assignment and Tracking - A Case Study on the Optimal Positioning of Tug Vessels along the Northern Norwegian Coast
Combining methodologies from cybernetics and artificial intelligence (AI), we present a receding horizon genetic algorithm (RHGA) for solving the task of dynamic assignment and tracking of multiple targets. We demonstrate the capabilities of the algorithm by means of a case study on optimal positioning of tugs to reduce the risk of oil tanker drifting accidents along the northern Norwegian coas...
متن کاملAn Improved Receding Horizon Genetic Algorithm For The Tug Fleet Optimisation Problem
A fleet of tugs along the northern Norwegian coast must be dynamically positioned to minimise the risk of oil tanker drifting accidents. We have previously presented a receding horizon genetic algorithm (RHGA) for solving this tug fleet optimisation (TFO) problem. In this paper, we begin by presenting an overview of the TFO problem and the details of the RHGA. Next, we identify and correct a fl...
متن کاملEvaluation Heuristics for Tug Fleet Optimisation Algorithms - A Computational Simulation Study of a Receding Horizon Genetic Algorithm
A fleet of tugs along the northern Norwegian coast must be dynamically positioned to minimise the risk of oil tanker drifting accidents. We have previously presented a receding horizon genetic algorithm (RHGA) for solving this tug fleet optimisation (TFO) problem. Here, we first present an overview of the TFO problem, the basics of the RHGA, and a set of potential cost functions with which the ...
متن کاملA Sustainable Model For Optimal Dynamic Allocation Of Patrol Tugs To Oil Tankers
Oil tanker traffic constitutes a vital part of the maritime operations in the High North and is associated with considerable risk to the environment. As a consequence, the Norwegian Coastal Administration (NCA) administers a number of vessel traffic services (VTS) centers along the Norwegian coast, one of which is located in the town of Vardø, in the extreme northeast part of Norway. The task o...
متن کاملLAGA: A Software for Landscape Allocation using Genetic Algorithm
In this paper, Landscape Allocation using Genetic Algorithm (LAGA), a spatial multi-objective land use optimization software is introduced. The software helps in searching for optimal land use when multiple objectives such as suitability, area, cohesion and edge density indices are simultaneously involved. LAGA is a flexible and easy to use genetic algorithm-based software for optimizing the sp...
متن کامل