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In this paper, a combinatorial optimisation algorithm inspired by the Physarum Polycephalum mould is presented and applied to the optimal trajectory planning of a multiple asteroid tour mission. The Automatic Incremental Decision Making And Planning (AIDMAP) algorithm is capable of solving complex discrete decision making problems with the use of the growth and exploration of the decision network...
The paper presents an Ant System based algorithm to optimally plan multi-gravity assist trajectories. The algorithm is designed to solve planning problems in which there is a strong dependency of one decision on all the previously-made decisions. In the case of multi-gravity assist trajectory planning, the number of possible paths grows exponentially with the number of planetary encounters. The proposed...
In many applications it can be advantageous for the decision maker to have multiple options available for a possible realization of the project. One way to increase the number of interesting choices is in certain cases to consider in addition to the optimal solution x* also nearly optimal or approximate solutions which differ in the design space from x* by a certain value. In this paper we address...
This paper presents an algorithm for multiobjective optimization that blends together a number of heuristics. A population of agents combines heuristics that aim at exploring the search space both globally and in a neighborhood of each agent. These heuristics are complemented with two restart mechanisms and a combination of a local and global archive. The hybrid algorithm is tested at first on a set...
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