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The grocery superstore vehicle scheduling problem

Research output: Working paper

Published

Standard

The grocery superstore vehicle scheduling problem. / Sohrabi, B; Mercer, A; Eglese, R W.

Lancaster University : The Department of Management Science, 2003. (Management Science Working Paper Series).

Research output: Working paper

Harvard

Sohrabi, B, Mercer, A & Eglese, RW 2003 'The grocery superstore vehicle scheduling problem' Management Science Working Paper Series, The Department of Management Science, Lancaster University.

APA

Sohrabi, B., Mercer, A., & Eglese, R. W. (2003). The grocery superstore vehicle scheduling problem. (Management Science Working Paper Series). The Department of Management Science.

Vancouver

Sohrabi B, Mercer A, Eglese RW. The grocery superstore vehicle scheduling problem. Lancaster University: The Department of Management Science. 2003. (Management Science Working Paper Series).

Author

Sohrabi, B ; Mercer, A ; Eglese, R W. / The grocery superstore vehicle scheduling problem. Lancaster University : The Department of Management Science, 2003. (Management Science Working Paper Series).

Bibtex

@techreport{5af8206a98054e57826e67d1fe725fac,
title = "The grocery superstore vehicle scheduling problem",
abstract = "Scheduling the deliveries from a regional distribution centre (RDC) to large stores of a major fmcg retailer includes every possible vehicle routing complexity. Usual constraints, like the size of the vehicle and the length of the driving day, apply. More importantly, loading feasibility is a major factor, with frozen goods being at the front, produce and perishable products in the middle, and groceries at the tail of the rear end loading vehicle. Moreover, these three product types have different time windows, determined store by store. Items like medium movers and alcoholic drinks may only be stocked at particular hub depots, from where they must be collected and then delivered to the retail outlets. Collections of salvage are made from the stores and goods from suppliers are backhauled to a RDC, which may not be the vehicle's base. Then there may be trunking between RDCs. In this case study, deliveries and collections by vehicles at a RDC are presently scheduled by updating daily a basic plan prepared every six months, using the skills of an experienced distribution professional. A simulated annealing based algorithm has been developed to speed up the process by circumventing the need for the skeletal schedule. In the application tested, the solution produced by the algorithm requires the same number of vehicles as actually used, though the total delivery time is slightly longer. Further improvements, particularly in the quality of the initial solution, may be possible by exploiting the problem structure in recognisable ways.",
keywords = "retail distribution, vehicle routing, simulated annealing",
author = "B Sohrabi and A Mercer and Eglese, {R W}",
year = "2003",
language = "English",
series = "Management Science Working Paper Series",
publisher = "The Department of Management Science",
type = "WorkingPaper",
institution = "The Department of Management Science",

}

RIS

TY - UNPB

T1 - The grocery superstore vehicle scheduling problem

AU - Sohrabi, B

AU - Mercer, A

AU - Eglese, R W

PY - 2003

Y1 - 2003

N2 - Scheduling the deliveries from a regional distribution centre (RDC) to large stores of a major fmcg retailer includes every possible vehicle routing complexity. Usual constraints, like the size of the vehicle and the length of the driving day, apply. More importantly, loading feasibility is a major factor, with frozen goods being at the front, produce and perishable products in the middle, and groceries at the tail of the rear end loading vehicle. Moreover, these three product types have different time windows, determined store by store. Items like medium movers and alcoholic drinks may only be stocked at particular hub depots, from where they must be collected and then delivered to the retail outlets. Collections of salvage are made from the stores and goods from suppliers are backhauled to a RDC, which may not be the vehicle's base. Then there may be trunking between RDCs. In this case study, deliveries and collections by vehicles at a RDC are presently scheduled by updating daily a basic plan prepared every six months, using the skills of an experienced distribution professional. A simulated annealing based algorithm has been developed to speed up the process by circumventing the need for the skeletal schedule. In the application tested, the solution produced by the algorithm requires the same number of vehicles as actually used, though the total delivery time is slightly longer. Further improvements, particularly in the quality of the initial solution, may be possible by exploiting the problem structure in recognisable ways.

AB - Scheduling the deliveries from a regional distribution centre (RDC) to large stores of a major fmcg retailer includes every possible vehicle routing complexity. Usual constraints, like the size of the vehicle and the length of the driving day, apply. More importantly, loading feasibility is a major factor, with frozen goods being at the front, produce and perishable products in the middle, and groceries at the tail of the rear end loading vehicle. Moreover, these three product types have different time windows, determined store by store. Items like medium movers and alcoholic drinks may only be stocked at particular hub depots, from where they must be collected and then delivered to the retail outlets. Collections of salvage are made from the stores and goods from suppliers are backhauled to a RDC, which may not be the vehicle's base. Then there may be trunking between RDCs. In this case study, deliveries and collections by vehicles at a RDC are presently scheduled by updating daily a basic plan prepared every six months, using the skills of an experienced distribution professional. A simulated annealing based algorithm has been developed to speed up the process by circumventing the need for the skeletal schedule. In the application tested, the solution produced by the algorithm requires the same number of vehicles as actually used, though the total delivery time is slightly longer. Further improvements, particularly in the quality of the initial solution, may be possible by exploiting the problem structure in recognisable ways.

KW - retail distribution

KW - vehicle routing

KW - simulated annealing

M3 - Working paper

T3 - Management Science Working Paper Series

BT - The grocery superstore vehicle scheduling problem

PB - The Department of Management Science

CY - Lancaster University

ER -