Solving the Travelling Thief Problem based on Item Selection Weight and Reverse Order Allocation

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Authors Lei Yang, Zitong Zhang, Xiaotian Jia, Peipei Kang, Wensheng Zhang, Dongya Wang arXiv ID 2012.08888 Category cs.AI: Artificial Intelligence Citations 5 Venue IEEE Access Last Checked 4 months ago
Abstract
The Travelling Thief Problem (TTP) is a challenging combinatorial optimization problem that attracts many scholars. The TTP interconnects two well-known NP-hard problems: the Travelling Salesman Problem (TSP) and the 0-1 Knapsack Problem (KP). Increasingly algorithms have been proposed for solving this novel problem that combines two interdependent sub-problems. In this paper, TTP is investigated theoretically and empirically. An algorithm based on the score value calculated by our proposed formulation in picking items and sorting items in the reverse order in the light of the scoring value is proposed to solve the problem. Different approaches for solving the TTP are compared and analyzed; the experimental investigations suggest that our proposed approach is very efficient in meeting or beating current state-of-the-art heuristic solutions on a comprehensive set of benchmark TTP instances.
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