Multi-Objective Optimization for the m-PDPTW: Aggregation Method With Use of Genetic Algorithm and Lower Bounds | Zendy

Imen Harbaoui Dridi | Zendy; Ryan Kammarti | Zendy; Mekki Ksouri | Zendy; Pierre Borne | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Multi-Objective Optimization for the m-PDPTW: Aggregation Method With Use of Genetic Algorithm and Lower Bounds

Author(s) -

Imen Harbaoui Dridi,

Ryan Kammarti,

Mekki Ksouri,

Pierre Borne

Publication year - 2011

Publication title -

international journal of computers communications and control

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.422

H-Index - 33

eISSN - 1841-9844

pISSN - 1841-9836

DOI - 10.15837/ijccc.2011.2.2172

Subject(s) - tardiness , computer science , mathematical optimization , genetic algorithm , pickup , routing (electronic design automation) , vehicle routing problem , algorithm , compromise , optimization problem , mathematics , job shop scheduling , artificial intelligence , computer network , image (mathematics) , social science , sociology

The PDPTW is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers in purpose to satisfy precedence, capacity and time constraints. We present, in this paper, a genetic algorithm for multi-objective optimization of a multi pickup and delivery problem with time windows (m-PDPTW), based on aggregation method and lower bounds. We propose in this sense a brief literature review of the PDPTW, present our approach to give a satisfying solution to the m-PDPTW minimizing the compromise between total travel cost and total tardiness time.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research