VEHICLE FLOW FORMULATION MODEL AND HYBRID ALGORITHM OF ADAPTIVE LARGE NEIGHBORHOOD SEARCH AND SIMULATED ANNEALING FOR SOLVING THE PICKUP AND DELIVERY PROBLEM WITH CROSS-DOCKING (PDPCD) CONSIDERING TIME WINDOWS AND HETEROGENEOUS FIXED-FLEET VEHICLES CONSTRAINTS
The Pickup and Delivery Problem with Cross Docking (PDPCD) is a logistic problem that involves the pickup and delivery of goods to a set of customer pairs. The vehicle routes selection in this problem aims to minimize transportation costs while considering at least one of two pickup and delivery...
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| Main Author: | |
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/79666 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The Pickup and Delivery Problem with Cross Docking (PDPCD) is a logistic problem
that involves the pickup and delivery of goods to a set of customer pairs. The vehicle
routes selection in this problem aims to minimize transportation costs while
considering at least one of two pickup and delivery strategies, namely direct shipping
and cross docking. This research proposes a mathematical model and a combined
algorithm of Adaptive Large Neighborhood Search (ALNS) and Simulated Annealing
(SA) which is developed based on several previous studies for solving PDPCD. Time
window constraints for customers and heterogeneous fix fleet vehicle constraints are
also introduced in this research. The results show that the proposed algorithm provides
a solution cost gap of 0.91% with a computation time 700 times faster than the optimal
solution in LINGO. Additionally, the ALNS-SA algorithm yields solution cost and
computation time reductions of 2.1% and 75.1%, respectively, compared to the cost
and computation time of the SA algorithm proposed by Suprayogi (2023) for the
PDPCD with time window and homogeneous vehicle constraints.
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