Solving the Pickup and Delivery Problem with Time Windows using "Squeaky Wheel" Optimization with Local Search

The Pickup and Delivery Problem with Time Windows (PDPTW) is an important problem in fleet planning where decisions can involve not only dispatching company fleets but also the selection of carriers on certain routes. In this problem, vehicles travel to a variety of locations to deliver or pick up g...

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Main Authors: LIM, Hongping, LIM, Andrew, RODRIGUES, Brian
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Language:English
Published: Institutional Knowledge at Singapore Management University 2002
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Online Access:https://ink.library.smu.edu.sg/lkcsb_research/1963
https://ink.library.smu.edu.sg/context/lkcsb_research/article/2962/viewcontent/SolvingPickupDeliveryProblemTimeWindows_2002.pdf
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spelling sg-smu-ink.lkcsb_research-29622018-07-09T07:43:40Z Solving the Pickup and Delivery Problem with Time Windows using "Squeaky Wheel" Optimization with Local Search LIM, Hongping LIM, Andrew RODRIGUES, Brian The Pickup and Delivery Problem with Time Windows (PDPTW) is an important problem in fleet planning where decisions can involve not only dispatching company fleets but also the selection of carriers on certain routes. In this problem, vehicles travel to a variety of locations to deliver or pick up goods and to provide services. The increasing costs for additional vehicles motivate managers to optimize fleet usage. Managers also seek to achieve economical use of fuel, maintenance and overtime costs by minimizing travel distance and duration. As such, PDPTW impacts the interface of supplier-customer relationship management in the supply chain process and is essential for any linked decision support system. In this paper, we describe deployment of a relatively new optimization technique, known as "Squeaky Wheel" Optimization (SWO), to the PDPTW. Our objective is to minimize the fleet size, travel distances, schedule durations and waiting times. We implement an SWO framework for the PDPTW, integrating Solomonís Insertion Heuristic and Local Search into a construction phase. In addition, we design a blame assignment and prioritizing schemes to facilitate problem solution. Our new method has been tested on the Solomonís 56 benchmark cases for which we have obtained encouraging results with this new technique. 2002-08-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/lkcsb_research/1963 https://ink.library.smu.edu.sg/context/lkcsb_research/article/2962/viewcontent/SolvingPickupDeliveryProblemTimeWindows_2002.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Vehicle routing squeaky wheel heuristics Operations and Supply Chain Management
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Vehicle routing
squeaky wheel
heuristics
Operations and Supply Chain Management
spellingShingle Vehicle routing
squeaky wheel
heuristics
Operations and Supply Chain Management
LIM, Hongping
LIM, Andrew
RODRIGUES, Brian
Solving the Pickup and Delivery Problem with Time Windows using "Squeaky Wheel" Optimization with Local Search
description The Pickup and Delivery Problem with Time Windows (PDPTW) is an important problem in fleet planning where decisions can involve not only dispatching company fleets but also the selection of carriers on certain routes. In this problem, vehicles travel to a variety of locations to deliver or pick up goods and to provide services. The increasing costs for additional vehicles motivate managers to optimize fleet usage. Managers also seek to achieve economical use of fuel, maintenance and overtime costs by minimizing travel distance and duration. As such, PDPTW impacts the interface of supplier-customer relationship management in the supply chain process and is essential for any linked decision support system. In this paper, we describe deployment of a relatively new optimization technique, known as "Squeaky Wheel" Optimization (SWO), to the PDPTW. Our objective is to minimize the fleet size, travel distances, schedule durations and waiting times. We implement an SWO framework for the PDPTW, integrating Solomonís Insertion Heuristic and Local Search into a construction phase. In addition, we design a blame assignment and prioritizing schemes to facilitate problem solution. Our new method has been tested on the Solomonís 56 benchmark cases for which we have obtained encouraging results with this new technique.
format text
author LIM, Hongping
LIM, Andrew
RODRIGUES, Brian
author_facet LIM, Hongping
LIM, Andrew
RODRIGUES, Brian
author_sort LIM, Hongping
title Solving the Pickup and Delivery Problem with Time Windows using "Squeaky Wheel" Optimization with Local Search
title_short Solving the Pickup and Delivery Problem with Time Windows using "Squeaky Wheel" Optimization with Local Search
title_full Solving the Pickup and Delivery Problem with Time Windows using "Squeaky Wheel" Optimization with Local Search
title_fullStr Solving the Pickup and Delivery Problem with Time Windows using "Squeaky Wheel" Optimization with Local Search
title_full_unstemmed Solving the Pickup and Delivery Problem with Time Windows using "Squeaky Wheel" Optimization with Local Search
title_sort solving the pickup and delivery problem with time windows using "squeaky wheel" optimization with local search
publisher Institutional Knowledge at Singapore Management University
publishDate 2002
url https://ink.library.smu.edu.sg/lkcsb_research/1963
https://ink.library.smu.edu.sg/context/lkcsb_research/article/2962/viewcontent/SolvingPickupDeliveryProblemTimeWindows_2002.pdf
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