dc.contributor.advisor |
Thibbotuwawa A |
|
dc.contributor.advisor |
Perera HN |
|
dc.contributor.author |
Fernando M |
|
dc.date.accessioned |
2022 |
|
dc.date.available |
2022 |
|
dc.date.issued |
2022 |
|
dc.identifier.citation |
Fernando, M. (2022). An Optimization model for multi-objective vehicle routing problem for perishable goods distribution [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/21667 |
|
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/21667 |
|
dc.description.abstract |
Vehicle Routing Problem (VRP) is a well-studied area of operations research that has resulted
in significant cost savings in global transportation. The primary goal of the VRP is to find the
best route plan that minimizes the total distance traveled. The current study used VRP to solve
the problem of fresh Agri products distribution in retail chains. With the advancement of
computation power, researchers pay more attention to incorporating real-world characteristics
when developing VRP, making it more practical for use in real-world applications. Existing
literature identifies a research gap in richer problems that use real-world characteristics
concurrently. This study created an integrated bi-objective VRP model that focused on
resource optimization, order scheduling, and route optimization all at the same time. Two
objectives aim to minimize distribution costs while ensuring product deliveries to retail outlets
on time. To improve real-world applicability, the model incorporated multiple real-world
characteristics simultaneously. All the algorithms were developed using an open-source
optimization library called OR-tools.
This research compared several heuristics and metaheuristic methods respectively, to obtain
the IBFS (Initial Basic Feasible Solutions) and iterative improvements. Thereafter, best
performing heuristic method (savings algorithms) and metaheuristic method (guided local
search) were hybridized to develop the proposed two-phase solution method. All the solution
algorithms and the developed VRP model were tested using the data obtained from one of the
largest retail chains in Sri Lanka. Numerical experiments show the efficiency of the proposed
solution algorithm in solving a real-world VRP problem. Further, numerical experiments show
that the proposed VRP model has achieved a 16% saving in daily distribution cost while
ensuring on-time deliveries to 95% of the retail outlets. Further, on-time deliveries of fresh
Agri products ensure the freshness conditions. The developed VRP model is efficient to use
as an operational planning tool for planning distribution operations in retail chains. |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
VEHICLE ROUTING PROBLEM |
en_US |
dc.subject |
PERISHABLE GOODS DISTRIBUTION |
en_US |
dc.subject |
RETAIL SUPPLY CHAIN |
en_US |
dc.subject |
HEURISTIC METHODS |
en_US |
dc.subject |
REAL-WORLD APPLICATION |
en_US |
dc.subject |
METAHEURISTIC METHODS |
en_US |
dc.subject |
TRANSPORT & LOGISTIC MANAGEMENT - Dissertation |
en_US |
dc.title |
An Optimization model for multi-objective vehicle routing problem for perishable goods distribution |
en_US |
dc.type |
Thesis-Abstract |
en_US |
dc.identifier.faculty |
Engineering |
en_US |
dc.identifier.degree |
MSc in Transport & Logistics Management by Research |
en_US |
dc.identifier.department |
Department of Transport & Logistics Management |
en_US |
dc.date.accept |
2022 |
|
dc.identifier.accno |
TH5035 |
en_US |