Solving a flexible resource-constrained project scheduling problem for an e-grocery fulfilment centre: a meta-heuristic approach

Master thesis Aerospace Engineering

Master thesis (2022)

Authors

J.B. van Teeffelen Aerospace Engineering

Contributors

A. Bombelli Air Transport & Operations - Aerospace Engineering (mentor)
M.D. Pavel (mentor)
M. Lourenço Baptista Air Transport & Operations - Aerospace Engineering (mentor)
F. Boekema (graduation committee member)
Faculty
Aerospace Engineering, Aerospace Engineering
Copyright: © 2022 Jop van Teeffelen
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Published Date

19-12-2022

Language

English

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Faculty

Aerospace Engineering

Abstract

The demand for online shopping has grown tremendously in the
last couple of years. Picnic, a major player in the online grocery industry, is
struggling to achieve long-term growth within its current operations. Scheduling
and planning are key drivers for maintaining operational efficiency. The
Fulfilment Centre (FC) and Distribution Centre (DC) costs heavily depend on
efficient operations. This research focuses on improving the scheduling process
in an e-grocery FC and DC. The main objective of the model is to maximise the quality
of the schedule, which is achieved through two lexicographical objectives.
First, the make span is minimised to improve efficiency and to calculate the
number of employees required to fulfil the workload. The make span of a
schedule is defined as the time between the first scheduled activity i and the
last activity j in a schedule s. Next, the number of switches between
activities is reduced. The second objective is to increase overall productivity
since switching moments cause slack in the operations. Two solution methods are
proposed to solve the Flexible Resource Constrained Project Scheduling Problem
(FRCPSP). The first solution method is a Mixed Integer Linear Programming
(MILP) formulation that is solved with a Branch & Cut (B&C) algorithm.
Next, a meta-heuristic is proposed named Variable Neighbourhood Search (VNS). The
initial solution is computed by solving the MILP for one objective, minimising
the make span. Next, the VNS uses nested neighbourhoods to modify the answer
resulting in fewer switches per schedule. For small instances, the exact
formulation outperforms the meta-heuristic in most cases. Conversely, the meta-
heuristic features a higher efficacy and efficiency when tackling more
significant instances, being the only solution method capable of yielding
feasible solutions for real-world scheduling problems. Despite the
effectiveness of the proposed meta-heuristic, some operational adjustments are
still required before implementing the proposed decision-making tool.