Abstract
This paper considers the non-smooth arc routing problem (NS-ARP) with soft constraints in order to capture in more perceptive way realistic constraints violations arising in transportation and logistics. To appropriately solve this problem, a biased-randomized procedure with iterated local search (BRILS) and a mathematical model for this ARP variant is proposed. An extensive computational study is conducted on rich and diverse problem instances. The results highlight the competitiveness of BRILS in terms of quality and time, where it provides high-quality solutions within reasonable computational times. In the context of real-world environments, the performance exhibited by BRILS motivates its incorporation in intelligent and integrative systems where frequent and fast solutions are required.
Original language | English |
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Pages (from-to) | 205-220 |
Number of pages | 16 |
Journal | Expert systems with applications |
Volume | 98 |
DOIs | |
Publication status | Published - 15 May 2018 |
Externally published | Yes |
Keywords
- Arc routing problem
- Biased-randomization
- Metaheuristics
- Non-smooth optimization
- Soft constraints