Research Kenneth Sörensen

Abstract

Increasingly, cities aim at improving the sustainability and efficiency of their urban supply chains, by restricting the use of certain vehicles or improving collaboration among supply chain actors. Additionally, new technologies and trends are emerging, e.g., micro consolidation centers, sidewalk robots, autonomous vehicles, synchromodality, etc. These trends generate a myriad of difficult intertwined strategic and operational decision problems. Currently, however, the optimization and simulation tools required to support decision-making in such a complex environment are (1) disjointed and scattered across the scientific literature, or (2) not mature enough to adequately handle emerging urban logistic trends. To bridge this gap in the literature, and to aid cities and supply chain actors in modelling and optimizing the supply chains, we propose to develop a comprehensive and complementary suite of urban logistics optimization algorithms for "the" city. These problems of optimizing urban supply chains are typically large-scale, multi-level and multi-objective. In order to appropriately model and solve these problems, significant advances in operations research techniques are required. They will ultimately contribute to improving the understanding of the impact of new technologies, trends, and policies for all urban logistics stakeholders, and support their decisions towards a more sustainable city.

Researcher(s)

• Promoter: Sörensen Kenneth

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

The goal of this project is to develop a suite of models and algorithms to optimize urban logistics operations. Different from other similar endeavors, our algorithms will focus specifically on the urban context and will take into account the measures taken by city administrations that have an impact on the logistics operations on their territory. Such measures might include car-free zones, specific parking spaces or time windows for truck deliveries, a ban on certain vehicles in certain areas, etc. The algorithms will allow for an evaluation of the impact of these measures in order to assist in reducing the negative effects of logistics operations on the livability of the city and to strengthen the competitiveness of the supply chain actors. Contrary to existing urban logistics optimization problems, the models developed in this project will be based on an in-depth economic analysis. The algorithms will be able to support both strategic, tactical, and operational decisions and will be usable by (1) a single company, (2) a coalition of cooperating companies, and (3) the city administration. The project focuses on four flows, i.e., important logistics streams within the city: waste collection, construction logistics (moving building materials into the city), hospitality and health logistics (deliveries of food and other products to hotels, bars, restaurants, retirement homes, etc.), and grocery delivery (from supermarkets and other food suppliers to individual customers). The algorithms will be developed for several specific logistics scenarios based on the supply chains operated by the companies collaborating in this project. They will, however, be generic enough to later be extended to other use cases. Methodologically, the algorithms developed in this project will be based on state-of-the-art heuristic optimization. An innovative aspect of this project is that we will develop a common trunk, i.e., a set of data models and algorithmic operators that are general enough to function across a wide range of use cases. This common trunk will allow for the rapid development of specific models and algorithms for the various scenarios. Furthermore, the algorithms and models developed in this project will optimize logistic flows while taking into account person mobility to properly account for the integrated city perspective. The specific results that will be realized by the project are summarized below. A suite of algorithms to optimize urban supply chains; for each of the four flows identified before, optimization algorithms will be developed and demonstrated. Whenever possible, these algorithms will be defined at the level of the common trunk. However, the algorithms will be fine-tuned to the specific needs of the logistic operations of each flow. Quantitative/economic analysis of collaboration opportunities; specifically for each of the four flows that are considered, the economics of operation of the supply chain actors are quantified, and the potential of optimized collaboration in a realistic setting (a chosen city) is assessed. Quantitative/economic assessment of mobility measures; for each of the four cities considered in this project, a list of potential logistics-oriented mobility measures is compiled. For each of the flows and cities, the impact of these mobility measures on the operations of supply chain actors is assessed. Decision support to optimize operations with respect to city mobility measures taking into account a company-level perspective as well as the societal perspective. Insight in and support for collaborative gain sharing; based on insights from the optimization simulations, interactions with supply chain actors and cities, and on research, alternatives of collaborative gain sharing will be compared and evaluated in light of fairness, complexity (ease of real-life implementation), and the ability to sustain independently of subsidies.

Researcher(s)

• Promoter: Sörensen Kenneth
• Co-promoter: Beckers Joris
• Co-promoter: Vanelslander Thierry

Research team(s)

• Engineering Management

Project type(s)

• Research Project

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)

• Promoter: Sörensen Kenneth
• Co-promoter: Cornelissens Trijntje

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

Frustration is a common emotion among regular bus users, as bus transport tends to be slow, inefficient, and inflexible. Typically, a bus service (i.e., a set of bus routes and timetables) remains the same throughout the day, even when the demand for bus transport varies considerably over time. The main reason for this inflexibility was that, until very recently, public bus operators had no way of knowing the demand for transportation at any given moment, and were therefore forced to use fixed bus schedules. This lack of knowledge is, however, likely to change with the advent of the "smart city". In the near future, sensors, mobile devices, and other smart city technology will empower public transport operators to roll out flexible bus services that respond to the actual demand for transportation, the current traffic conditions, etc. Also the on-line communication between potential passengers and bus operators, in both directions, will work smoothly. This increases the number of opportunities to improve and tailor the route, stops or timetable of a bus line, also during operations. The aim of this project is to develop the optimization models and algorithms to fully exploit these opportunities and to evaluate the added value of flexible services over conventional fixed-line fixedtimetable services. The goal is to obtain a flexible and demand oriented public transport system which is more efficient from an operator cost perspective and sustainable from a societal perspective.

Researcher(s)

• Promoter: Sörensen Kenneth

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

Purpose of this research project is to investgate the diferent characteristcs and needs of the vessel trafc towards the port of Antwerp. Data analysis will permit us to predict beter the intensity of the trafic and to have beter insight into the capacity needed to minimize the delays of the nautcal services at peak moments. We want to create a beter efcient system for each needed service by a nautcal actor. This will have its efect on the investment policies. The optmalisaton of the efciency and the capacity is dependable of the service level that one want to deliver to the trafc and are important strategical questons for the management of the nautcal actors. So by further data analysis one want to have a beter view on the trafc prognosis so to have a beter monitoring of the performance of the nautcal chain for example to investgate the delays of vessel travel tme because of the shortage of pilots at peak moments, to investgate the lock-capacity of the Antwerp Harbor so to avoid delays at peak moments (for example at end of work shifs of harbor workers), and to investgate the capacity of the tug ships inside the harbor of Antwerp

Researcher(s)

• Promoter: Sörensen Kenneth

Research team(s)

• Engineering Management

Project type(s)

• Research Project

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)

• Promoter: Cornelissens Trijntje
• Co-promoter: Sörensen Kenneth
• Fellow: Gamez Alban Harol Mauricio

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

Recently, the Flemish weekly magazine Knack published a scathing article entitled "Pamphlet of an angry bus traveler: The 10 pests of De Lijn", in which it decried (among other things) the inefficiency of public bus transport. One of the main reasons for this inefficiency: buses run along fixed routes, following fixed time schedules, both of which are defined not knowing where (potential) passengers are, where they want to go, and when they would like to arrive. As a result, some buses run empty, whereas others are jam-packed with frustrated passengers. The ubiquity of mobile devices would, for the first time in human history, allow for a large-scale shift to on-demand public transport in which buses drive along routes completely determined by requests for transportation. In such a system, when a passenger wants to move from one place to another she indicates her departure and arrival locations, as well as a preferred time of arrival. Planning all of these transportation requests, however, is a daunting task, for which adequate models and algorithms have not yet been developed. This project focuses on the optimization problem that arises when bus routes in an urban environment are determined entirely based on transportation requests issued by potential passengers. We call this novel problem the On-Demand Bus Routing Problem (ODBRP) and will develop efficient algorithms for its different variants.

Researcher(s)

• Promoter: Sörensen Kenneth
• Fellow: Melis Lissa

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

Local public transport, defined as the collective scheduled transport of passengers, is one of the backbones of urban mobility within the EU. The traditional line-based bus system used in virtually every city worldwide, however, is inherently inefficient and lacks flexibility. Even though many obstacles still need to be overcome, the ubiquity of mobile devices would for the first time in human history allow for a large-scale shift to on-demand public transport. However: the operational and tactical foundations that are required to implement an on-demand transportation system are still lacking. Even though a large majority of people now has the technological means to determine exactly where they are and transmit exactly where they want to go, the tools to plan all of these transportation requests have not been developed. Such a system would demand carrying out optimization on a scale never seen before, and will require not only modeling all the intricacies of an on-demand scheduling of passengers, but to develop new optimization algorithms and software components that can coordinate such a massive fleet of vehicles and vast number of passengers. The main objective of this project is to develop the Operations Research foundations that will allow to design and deploy a fully on-demand public transportation system. The outcome of this project will provide an optimization framework for the scheduling of passengers and buses, a simulation environment to evaluate the impact of several design/operational decisions on the performance of the transportation system, and a set of tactical guidelines that will assist the progressive transition to an on-demand operation. Achieving these goals will position the University of Antwerp as one of the first research centers to tackle this paramount challenge.

Researcher(s)

• Promoter: Sörensen Kenneth

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

The aim of this project is to study the effect of inventory policy and its interactions with vehicle routing in horizontal collaborations of different companies. This will be done through a series of rigorously designed experiments, using statistical design of experiments methodology.

Researcher(s)

• Promoter: Sörensen Kenneth
• Co-promoter: Goos Peter
• Fellow: Palhazi Cuervo Daniel

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

Optimization problems abound in a wide variety of business environments, ranging from logistics and supply chain management, to the financial sector and health care. Companies in these areas support many of their decisions on powerful optimization methods. By doing so, they are able to become not only more profitable and competitive, but also more environmentally friendly. Metaheuristics are considered to be the dominant approach to tackle most optimization problems found in practice. However, they completely lack a scientifically sound methodology to analyze the optimization they carry out. All existing methodologies are based on the flawed principle of an algorithmic race: metaheuristics are evaluated at a single and arbitrary point in time only. Optimization is, however, not a race but a complex process that deserves a thorough assessment during its entire execution. It turns out that an analysis with these considerations has been carried out for over 40 years in clinical research. This approach, called longitudinal analysis, is commonly used to evaluate trials for determining the effectiveness of new treatments (in which several individuals are examined multiple times). The main goal of this proposal is to develop a sound methodology, based on the rigorous approach of longitudinal analysis, to evaluate (meta)heuristics. The methodology will be implemented as an open source software package, to allow researchers to apply it in a straightforward and userfriendly way.

Researcher(s)

• Promoter: Sörensen Kenneth

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

The main goal of this research is to develop vehicle routing algorithms for collaborative vehicle routing problems that can support logistics decision-making in horizontal coalitions of distribution companies. The algorithms will enable these coalitions to plan their joint operational "milk-run" distribution, but will also allow them to answer related tactical questions with respect to the contribution to the coalition gain of the (potential) partners in the coalition.

Researcher(s)

• Promoter: Sörensen Kenneth
• Fellow: Defryn Christof

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

This project represents a research contract awarded by the University of Antwerp. The supervisor provides the Antwerp University research mentioned in the title of the project under the conditions stipulated by the university.

Researcher(s)

• Promoter: Meersman Hilde
• Co-promoter: De Borger Bruno
• Co-promoter: Sörensen Kenneth
• Co-promoter: Van de Voorde Eddy
• Co-promoter: Verhetsel Ann

Research team(s)

• Transport and Regional Economics

Project type(s)

• Research Project

Abstract

Water distribution system design optimization is a heavily researched area in the field of hydraulics. This research is limited to theoretical, unnecessary complicated models, which can not be used in reallife applications. The aim is to develop a practical tool, that can support water distribution companies in taking network design decisions.

Researcher(s)

• Promoter: Sörensen Kenneth
• Fellow: De Corte Annelies

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

In this project we therefore propose a novel approach that tackles the bicycle repositioning problem by decomposing it into two distinct subproblems, and developing innovative algorithms for both of them: (1) the generation of loading or unloading requests, and (2) the (dynamic) assignment of these requests to vehicles and the scheduling of requests within each vehicle.

Researcher(s)

• Promoter: Sörensen Kenneth

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

The main goal of this research is to develop vehicle routing algorithms for collaborative vehicle routing problems that can support logistics decision-making in horizontal coalitions of distribution companies. The algorithms will enable these coalitions to plan their joint operational "milk-run" distribution, but will also allow them to answer related tactical questions with respect to the contribution to the coalition gain of the (potential) partners in the coalition.

Researcher(s)

• Promoter: Sörensen Kenneth
• Fellow: Defryn Christof

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

The main objectives of this project are: - Bring together the available Belgian expertise on combinatorial optimization problems, exploit synergies between the partner research groups, and create a network with a sufficient mass to attract young and experienced top-level scientists in Belgium, and further financing for research in the field. - Train young researchers in the field of combinatorial optimization. - Develop new models, algorithmic techniques and implementations for complex, large-scale combinatorial optimization problems. - Develop new international collaborations with other large teams working in the field of combinatorial optimization.

Researcher(s)

• Promoter: Sörensen Kenneth

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

Water distribution system design optimization is a heavily researched area in the field of hydraulics. This research is limited to theoretical, unnecessary complicated models, which can not be used in reallife applications. The aim is to develop a practical tool, that can support water distribution companies in taking network design decisions.

Researcher(s)

• Promoter: Sörensen Kenneth
• Fellow: De Corte Annelies

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

The main goal of this research is to develop vehicle routing algorithms for collaborative vehicle routing problems that can support logistics decision-making in horizontal coalitions of distribution companies. The algorithms will enable these coalitions to plan their joint operational "milk-run" distribution, but will also allow them to answer related tactical questions with respect to the contribution to the coalition gain of the (potential) partners in the coalition.

Researcher(s)

• Promoter: Sörensen Kenneth
• Fellow: Defryn Christof

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

This project represents a formal research agreement between UA and on the other hand FISCH. UA provides FISCH research results mentioned in the title of the project under the conditions as stipulated in this contract.

Researcher(s)

• Promoter: Sörensen Kenneth
• Co-promoter: Cool Pegie
• Co-promoter: Maes Bert
• Co-promoter: Meynen Vera

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

Determining the optimal configuration of a distribution network for gas or water gives rise to a complex optimization problem, one of the reasons being that the feasibility and economic cost of a certain configuration can only be determined using simulation. In this project we will develop efficient optimization methods (metaheuristics) for this type of problem. The methods will be tested and applied in collaboration with distribution network administration companies.

Researcher(s)

• Promoter: Sörensen Kenneth
• Co-promoter: Mertens Luc

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

The project aims to develop a generic mechanism for coordination between departments in order to achieve a "collaborative supply chain management". By providing dynamic interaction between the various parties in the supply chain network an improved overall planning can be achieved. PearlChain.net's software is already generically built according to the "model-based" principle (departments, resources, capabilities, capacities, etc.). The system to generically negotiate between departments, customers and suppliers has yet to be developed. This project will aim to develop an innovative method to coordinate between various department-specific production planning problems within a supply chain alignment, but without creating a "global" actor who oversees the entire planning. The tuning of a specific production unit, will instead be achieved by communication / coordination between different departments. The interaction between departments should lead to reduced stock and reduced production time. The goal is to increase the efficiency and effectiveness of the production process (Supply Chain) between various parties.

Researcher(s)

• Promoter: Sörensen Kenneth

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

Horizontal collaboration among distributors is one of the most promising approaches to decrease supply chain costs and increase supply chain sustainability. However, effective joint supply chain planning is more complicated and requires methods and tools for operational planning that are able to distribute the gains that arise from collaboration fairly, rewarding flexibility. This research aims to develop such a profit allocation method and integrate it in a tool using metaheuristic to create an efficient operational plan.

Researcher(s)

• Promoter: Sörensen Kenneth
• Fellow: Vanovermeire Christine

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

This project represents a formal research agreement between UA and on the other hand GS1 Belgium & Luxembourg. UA provides GS1 Belgium & Luxembourg research results mentioned in the title of the project under the conditions as stipulated in this contract.

Researcher(s)

• Promoter: Sörensen Kenneth

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

Currently, no usable methods exist to solve dangerous goods vehicle routing problems while taking into account both economical and safety criteria. This research therefore aims at two innovations: (1) the development of a novel method for multi-objective optimization, that integrates a multi-criteria method into a multi-objective metaheuristic, and (2) the application of this method to one or more real-life vehicle routing problems.

Researcher(s)

• Promoter: Sörensen Kenneth
• Co-promoter: Springael Johan

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

This is a fundamental research project financed by the Research Foundation - Flanders (FWO). The project was subsidized after selection by the FWO-expert panel.

Researcher(s)

• Promoter: Sörensen Kenneth
• Co-promoter: Goos Peter

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

This project represents a research contract awarded by the University of Antwerp. The supervisor provides the Antwerp University research mentioned in the title of the project under the conditions stipulated by the university.

Researcher(s)

• Promoter: Sörensen Kenneth
• Fellow: Busschaert Sylvie

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

Both the industrial and the service sector are enthusiastic to perform fundamental research on decision support in cooperation with an academic partner. In this research, techniques from the broad area of OR/MS (operations research/management science) are used to support decisions on different levels (strategic to operational). This initial grant is an excellent occasion to build this multidisciplinary line of research, that aligns with several departments of the Faculty of Applied Economics of the Universiteit Antwerpen.

Researcher(s)

• Promoter: Sörensen Kenneth

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

Both the industrial and the service sector are enthusiastic to perform fundamental research on decision support in cooperation with an academic partner. In this research, techniques from the broad area of OR/MS (operations research/management science) are used to support decisions on different levels (strategic to operational). This initial grant is an excellent occasion to build this multidisciplinary line of research, that aligns with several departments of the Faculty of Applied Economics of the Universiteit Antwerpen.

Researcher(s)

• Promoter: Sörensen Kenneth
• Fellow: Sörensen Kenneth

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

This projects aims at developing novel search algorithms for finding optimal experimental designs. For that purpose, the newest methods for combinatorial optimization in operational research, involving metaheuristics, will be used in a new application area, the design of experiments. Both problems with a single objective as problems withmultiple objectives will receive our attention.

Researcher(s)

• Promoter: Goos Peter
• Co-promoter: Sörensen Kenneth

Research team(s)

• Engineering Management

Project type(s)

• Research Project

Abstract

The goals of this project are (1) to develop a branch-and-price algorithm based on a suitable mathematical programming formulation, in order to solve small and medium sized instances and (2) to develop a metaheuristic to quickly find good solutions to large-scale instances.

Researcher(s)

• Promoter: Goos Peter
• Co-promoter: Sörensen Kenneth

Research team(s)

• Engineering Management

Project type(s)

• Research Project