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The multi-product vehicle routing problem with cross-docking: a novel strategy hybrid bat algorithm for Industry 3.5 in Thailand's food industry


[ 1 ] Instytut Logistyki, Wydział Inżynierii Zarządzania, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[6.6] Management and quality studies

Year of publication


Published in

International Journal of Logistics Research and Applications

Journal year: 2022 | Journal volume: in press

Article type

scientific article

Publication language


  • Vehicle routing
  • metaheuristic
  • mathematical model
  • cross-docking
  • multiple products

EN This paper presents a multi-product vehicle routing problem with crossdocking operations for food industry to ensure products which can be delivered in time and with minimum transportation and hiring costs to perform for both supplier side and customer side. The problem was formulated as a special multi-product vehicle routing problem with cross-docking and time window constraints (MPVRPCDTW). A novel strategy hybrid based on the Bat algorithm (NSHBA) is presented to solve the MPVRPCDTW for the sustainable food industry by minimising the transportation cost and the number of vehicles, using the poultry industry as a case study. Additionally, a new disturbance algorithm (DA) was developed to find the best neighbourhood strategy to increase the efficiency and quality of solutions in the NSHBA. The computational results revealed that the NSHBA-DA outperformed the Bat algorithm, the differential evolution algorithm, and the particle swarm optimisation algorithm. The MATLAB App architecture based on all eight algorithms was designed and developed. The overall result of this study should prove to benefit the logistics staff in making the right decisions on cross-docking transportation by employing real-time data.

Date of online publication


Pages (from - to)

1 - 25




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