Research team

Expertise

My research is situated in Supply Chain and Operations Management and addresses the alignment of the design of the facilities and planning of the operations of an industrial company with its business strategy. This research is conducted in close collaboration with industrial contacts and the ANT/OR research group of the FBE department of Engineering Management. This research targets developing new mathematical models and solution methods by using techniques such as mathematical programming, metaheuristics and constraint programming. The data instances are based on realistic examples of industrial situations. The main target is building industrial decision support tools with academic rigour. Two main topics are addressed. Firstly, we focus on the strategic design of (chemical) batch plants and aim to complete earlier cost-based models with state-of-the-art performance measures such as reliability, responsiveness and flexibility of the operations. Secondly, the strategic design of e-commerce warehouses is challenged, trying to optimise the advantages of both human and automated operators.

OR4Logistics. 01/01/2021 - 31/12/2025

Abstract

This WOG brings together a large network of renowned experts in the OR community that are working on real-world logistics optimization problems. By sharing knowledge we can contribute to closing that gap between research and practice and have a significant impact on the efficiency and sustainability of the logistics sector. Applications drive research and often require solving ever larger and more complex models of real-world optimization problems.

Researcher(s)

Research team(s)

Project type(s)

  • Research Project

Introducing the concept of responsive and reliable delivery lead times in the strategic design of batch production plants for the chemical industry. 01/01/2019 - 31/12/2022

Abstract

Over the years, design models for production plants were mainly based on optimising capital and operational costs. Nowadays, responsive delivery lead times and reliable delivery are state-of-theart and equally important strategic management objectives. The aim of this project is to incorporate the supply chain performance attributes "responsiveness" and "reliability" into the mathematical optimisation models for strategic design of chemical batch production plants. At strategic level, the design of such batch plants defines the configuration (number and size of batch equipment), the size of the production batches for the different products and the production planning policy to be used. Depending on the production environment (Make-To-Order or Make-To-Stock), mode of operation (cyclic or non-cyclic) and design options (parallel equipment, dedicated and temporary storage tanks, or parallel production lines), different models will be defined. Small design problems will be optimised with exact mathematical programming techniques. For real size problems, efficient metaheuristics will be developped. Finally, the outcome of the different models will be used to align the appropriateness of strategic choices in plant design with specific business circumstances.

Researcher(s)

Research team(s)

Project type(s)

  • Research Project

Vehicle Routing Algorithms for Automated Warehouse Environments. 01/10/2018 - 30/09/2022

Abstract

The operational planning of pickup and drop-off activities in warehouses is currently done either manually, or using simple heuristics. Yet, mathematically, routing forklifts or AGVs in a warehouse is partly similar to routing vehicles on the road. In stark contrast to the absence of research on planning of vehicles in a warehouse, research on vehicle routing has yielded a rich literature describing a wide range of problem variants and advanced algorithms to solve them. The innovation of this project lies in the fact that it is one of the very first attempts to exploit the similarities between both research domains in order to improve the state of the art in the operational planning of warehouse operations. We focus on a specific vehicle routing problem (the full-truckload pickup and delivery problem) that has never before been studied in a warehouse context, take the best algorithms from the literature and adapt those algorithms to the specific requirements and constraints of AGV routing in a warehouse. We are the first to take such an approach. The resulting problem, that we have called the transport request scheduling problem (TRSP), along with its variants, will help warehouse managers and software developers of warehouse management systems in successfully planning their AGV operations.

Researcher(s)

Research team(s)

Project type(s)

  • Research Project

Optimisation of batch plant design: mathematical models and algorithms for strategic decision support 01/10/2017 - 30/09/2019

Abstract

This research project focuses on the impact of supply chain strategy on the design of multi-product chemical batch plants. Strategic design covers equipment choice, number and size, combined with tactical guidelines for the operational planning . Although highly interwoven, past research barely integrates plant design with supply chain strategies. The aim of this research is to develop mathematical models and a heuristic solution methods for this multi-objective optimization problem and to translate the results into comprehensive decision support guidelines for industry.

Researcher(s)

Research team(s)

Project type(s)

  • Research Project

Optimisation of batch plant design: mathematical models and algorithms for tactical decision support. 01/10/2015 - 30/09/2017

Abstract

This research project focuses on the impact of supply chain strategy on the tactical design of multiproduct chemical batch plants. Tactical design covers plant configuration as well as equipment choice, number, size, as layout of the pipeline network. Although highly interwoven, past research barely integrates plant design and supply chain or production strategies. The aim of this research is to gradually develop a mathematical model and a heuristic solution method for this multi-objective plant design optimisation problem and to translate the results into comprehensive industrial decision support guidelines.

Researcher(s)

Research team(s)

Project type(s)

  • Research Project