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Ant colony optimization algorithm for pickup and delivery problem with time windows

Abstract : This paper presents an efficient meta-heuristic for the Pickup and Delivery Problem with Time Windows (PDPTW) based on Ant Colony Optimization coupled to dedicated local search algorithms. The objective function is the minimization of the number of vehicles and the minimization of the total distance travelled. In PDPTW, the demands are coupled and every couple is a request which must be satisfy in the same route. Thus, the feasible solution space is tightly constraint and then makes the design of effective heuristics more difficult. Experimental results on 56 instances of 100 customers of Li and Lim’s benchmark show that the ACO coupled with PDPTW dedicated local search algorithms outperform existing algorithms. It returns in 98.2% (55/56) of cases a solution better or equal to the best known solution, and find a better solution than the best know in 44.6% (25/56).
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Conference papers
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Submitted on : Friday, February 21, 2020 - 9:07:20 AM
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Moïse Noumbissi Tchoupo, Alice Yalaoui, Lionel Amodeo, Farouk Yalaoui, F. Lutz. Ant colony optimization algorithm for pickup and delivery problem with time windows. XLVII Annual meeting of AIRO-Italian Operations Research Society, Sep 2017, Sorrente, Italy. ⟨10.1007/978-3-319-67308-0_19⟩. ⟨hal-02486533⟩



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