Multi depot dynamic vehicle routing problem with stochastic road capacity for emergency medical supply delivery in humanitarian logistics
As part of humanitarian logistics research for emergency medical supply delivery during disaster, the modelling and solution of a Multi Depot Dynamic Vehicle Routing Problem with Stochastic Road Capacity (MDDVRPSRC) is presented. Based on the chaotic setting from a disaster event, the model and s...
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| Format: | Thesis |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/104545/1/WadiPhdThesisV91_B5_FINAL%20-%20IR.pdf http://psasir.upm.edu.my/id/eprint/104545/ |
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| Summary: | As part of humanitarian logistics research for emergency medical supply delivery
during disaster, the modelling and solution of a Multi Depot Dynamic Vehicle Routing
Problem with Stochastic Road Capacity (MDDVRPSRC) is presented. Based
on the chaotic setting from a disaster event, the model and solution proposed are
validated and analysed through a Decision Support System (DSS), MDDVRPSRC
DSS. The model proposed is based on Markov Decision Processes (MDP) modelling
framework as part of reinforcement learning (RL) solution approach. Through this
model, multi objectives, multi depot, multi trip and split delivery among homogeneous
fleet of vehicle are addressed. Moreover a stochastic road capacity distribution
where its mean deteriorates over time is also depicted in the problem.
To solve the proposed model, an Approximate Dynamic Programming (ADP) approach
is applied focusing on the lookahead approach. Specifically a PDS - Rollout
Algorithm (PDS-RA) is adopted. Five variants of constructive base heuristics, Teach
Based Insertion Heuristic (TBIH-1 - TBIH-5) are proposed complementing the PDSRA
when dealing with the lookahead rollout involving stochastic road capacity.
The computational results obtained are compared with a matheuristic approach.
From this novel method, exact CPLEX computation is executed at every rollout
decision epoch, based on two proposed reduced 2-stage stochastic programming
ILP models (MDVRPSRC-2S1 and MDVRPSRC-2S2). These two models are derived
from the Multi Depot Vehicle Routing Problem with Stochastic Road Capacity
(MDVRPSRC-2S) which is proposed next to the deterministic model of Multi Depot
Vehicle Routing Problem with Road Capacity (D-MDVRPRC) stemming from the
preliminary research, prior to the development of MDDVRPSRC model. Results indicate
comparable quality of solution from the proposed heuristics to that of CPLEX
in random setting of the problem instances. In addition, the proposed heuristics are
especially superior in computation time.
The contributions of the research are as follows: (1) The MDP model for MDDVRPSRC,
deterministic D-MDVRPRC as well as 2 stage stochastic ILP MDVRPSRC-2S
models are respectively developed and presented; (2) based on the MDVRPSRC-
2S it is shown how 2-stage stochastic programming model can be applied through
CPLEX execution during each of Monte Carlo simulated PDS - RA by proposing
another two models as two reduced version (MDVRPSRC-2S1 and MDVRPSRC-
2S2) of the MDVRPSRC-2S; (3) the radial tremor disaster dispersion from a single
or multiple epicentres and the corresponding deterioration of road capacity distribution
mean and travel time are proposed; (4) the solution algorithm: TBIH-1, and it’s
4 variants (TBIH-2, TBIH-3, TBIH-4 and TBIH-5) are presented; (5) test dataset is
developed consists of simulated road networks and the damage unit of each roads
due to the earthquake for experimentation and simulation purposes, and finally (6) a
decision support system (MDDVRPSRC DSS) for simulating online delivery operation
during disaster is designed. All of these could be applied to all types of dynamic
vehicle routing problem involving any types of disaster and it’s inherent stochastic
road capacity as well as increased delayed travel time. |
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