Kevin Tierney

Kevin Tierney
Bielefeld University · Faculty of Business Administration and Economics

PhD

About

68
Publications
10,163
Reads
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1,275
Citations
Additional affiliations
April 2018 - present
Bielefeld University
Position
  • Professor (Full)
October 2013 - March 2018
Universität Paderborn
Position
  • Professor (Assistant)
November 2012 - March 2013
University of Hamburg
Position
  • Visiting PhD Student
Education
June 2010 - May 2013
September 2008 - May 2010
Brown University
Field of study
  • Computer science
September 2004 - March 2008
Rochester Institute of Technology
Field of study
  • Computer science

Publications

Publications (68)
Article
Full-text available
Roll-on roll-off (RoRo) shipping plays an important role in freight transport on the European continent, and is faced with the challenge of reducing its CO 2 emissions while increasing its efficiency. Dual cycling, in which loading and discharging processes are carried out simultaneously, achieves this goal by reducing the turnaround time of vessel...
Preprint
Full-text available
Algorithm configuration (AC) is concerned with the automated search of the most suitable parameter configuration of a parametrized algorithm. There is currently a wide variety of AC problem variants and methods proposed in the literature. Existing reviews do not take into account all derivatives of the AC problem, nor do they offer a complete class...
Preprint
Full-text available
This paper reports on the first international competition on AI for the traveling salesman problem (TSP) at the International Joint Conference on Artificial Intelligence 2021 (IJCAI-21). The TSP is one of the classical combinatorial optimization problems, with many variants inspired by real-world applications. This first competition asked the parti...
Chapter
We consider black-box optimization in which only an extremely limited number of function evaluations, on the order of around 100, are affordable and the function evaluations must be performed in even fewer batches of a limited number of parallel trials. This is a typical scenario when optimizing variable settings that are very costly to evaluate, f...
Article
Liner shipping repositioning is the costly process of moving container ships between services in a liner shipping network to adjust the network to the changing demands of customers. Existing deterministic models for the liner shipping fleet repositioning problem (LSFRP) ignore the inherent uncertainty present in the input parameters. Assuming these...
Chapter
We present PyDGGA, a Python tool that implements a distributed version of the automatic algorithm configurator GGA, which is a specialized genetic algorithm to find high quality parameters for solvers and algorithms. PyDGGA implements GGA using an event-driven architecture and runs a simulation of future generations of the genetic algorithm to maxi...
Preprint
Full-text available
Recently numerous machine learning based methods for combinatorial optimization problems have been proposed that learn to construct solutions in a sequential decision process via reinforcement learning. While these methods can be easily combined with search strategies like sampling and beam search, it is not straightforward to integrate them into a...
Preprint
Full-text available
We consider black-box optimization in which only an extremely limited number of function evaluations, on the order of around 100, are affordable and the function evaluations must be performed in even fewer batches of a limited number of parallel trials. This is a typical scenario when optimizing variable settings that are very costly to evaluate, f...
Article
Full-text available
The weather has a major impact on the profitability, safety, and environmental sustainability of the routes sailed by seagoing vessels. The prevailing weather strongly influences the course of routes, affecting not only the safety of the crew, but also the fuel consumption and therefore the emissions of the vessel. Effective decision support is req...
Article
Full-text available
The original version of this article has unfortunately contained an error in the Acknowledgement section.
Article
Liner carriers must regularly adjust their shipping networks to respond to competitors and changing seasonal customer demands. They do this by selecting and moving ships between routes. State-of-the-art approaches decompose this into two separate problems. We propose an integrated mathematical model and matheuristic for the liner shipping fleet dep...
Conference Paper
We address a milk run logistics problem in which goods must be transferred between facilities on a regular basis to support a company's production. The resulting optimization problem is a form of cyclical, multi-commodity inventory routing problem with pickups and deliveries. This problem becomes particularly challenging when either all available c...
Conference Paper
Inland shipping is a critical part of the global transport network that links population centers over rivers for both cargo and passenger transportation. Inland ships follow tight schedules, leaving little time for required maintenance or emergency repairs. Maintenance providers must therefore send their technicians out to ships during the ships' o...
Article
Dynamic pricing can be used for better fleet distribution in free-floating vehicle sharing (FFVS), and thus increase utilization and revenue for the provider by reducing supply-demand asymmetry. Supply-demand asymmetry refers to the existence of an undersupply of vehicles at some locations at the same time as underutilization of vehicles at other l...
Chapter
We address a milk run logistics problem in which goods must be transferred between facilities on a regular basis to support a company’s production. The resulting optimization problem is a form of cyclical, multi-commodity inventory routing problem with pick-ups and deliveries. This problem becomes particularly challenging when either all available...
Chapter
Inland shipping is a critical part of the global transport network that links population centers over rivers for both cargo and passenger transportation. Inland ships follow tight schedules, leaving little time for required maintenance or emergency repairs. Maintenance providers must therefore send their technicians out to ships during the ships’ o...
Conference Paper
Learning how to automatically solve optimization problems has the potential to provide the next big leap in optimization technology. The performance of automatically learned heuristics on routing problems has been steadily improving in recent years, but approaches based purely on machine learning are still outperformed by state-of-the-art optimizat...
Chapter
The goal of automatic algorithm configuration is to recommend good parameter settings for an algorithm or solver on a per-instance basis, i.e., for the specific problem instance being solved. Realtime algorithm configuration is a practically motivated variant of algorithm configuration, in which the problem instances arrive in a sequential manner a...
Chapter
We consider the dialectic search paradigm for box-constrained, non-linear optimization with heterogeneous variable types. In particular, we devise an implementation that can handle any computable objective function, including non-linear, non-convex, non-differentiable, non-continuous, non-separable and multi-modal functions. The variable types we c...
Article
The pre-marshalling problem has been extensively studied in recent years with the aim of minimizing the number of movements needed to rearrange a bay of containers. Time is a more realistic objective for measuring process efficiency, and we show that it does not correlate with the number of movements. As a result, we study the problem of minimizing...
Preprint
Full-text available
Learning how to automatically solve optimization problems has the potential to provide the next big leap in optimization technology. The performance of automatically learned heuristics on routing problems has been steadily improving in recent years, but approaches based purely on machine learning are still outperformed by state-of-the-art optimizat...
Article
One of the key challenges for operations researchers solving real-world problems is designing and implementing high-quality heuristics to guide their search procedures. In the past, machine learning techniques have failed to play a major role in operations research approaches, especially in terms of guiding branching and pruning decisions. We integ...
Chapter
Full-text available
We propose a new framework for decision making under uncertainty to overcome the main drawbacks of current technology: modeling complexity, scenario generation, and scaling limitations. We consider three NP-hard optimization problems: the Stochastic Knapsack Problem (SKP), the Stochastic Shortest Path Problem (SSPP), and the Resource Constrained Pr...
Article
Full-text available
We introduce three mathematical models of increasing complexity for designing liner shipping services that guarantee the punctual arrival of vessels at a specified service level. On-time reliability is an important performance indicator for many liner carriers, but current approaches for creating new routes in liner shipping networks do not conside...
Conference Paper
Full-text available
We propose a new framework for decision making under uncertainty to overcome the main drawbacks of current technology: modeling complexity, scenario generation, and scaling limitations. We consider three NP-hard optimization problems: the Stochastic Knapsack Problem (SKP), the Stochastic Shortest Path Problem (SSPP), and the Resource Constrained Pr...
Article
The container pre-marshalling problem involves the sorting of containers in stacks so that there are no blocking containers and retrieval is carried out without additional movements. This sorting process should be carried out in as few container moves as possible. Despite recent advancements in solving real world sized problems to optimality, sever...
Chapter
Full-text available
Local search metaheuristics have been developed as a general tool for solving hard combinatorial search problems. However, in practice, metaheuristics very rarely work straight out of the box. An expert is frequently needed to experiment with an approach and tweak parameters, remodel the problem, and adjust search concepts to achieve a reasonably e...
Chapter
We revisit algorithm selection for declarative programming solvers. We introduce two main ideas to improve cost-sensitive hierarchical clustering: First, to augment the portfolio builder with a self-configuration component. And second, we propose that the algorithm selector assesses the confidence level of its own prediction, so that a more defensi...
Article
Increasing urbanization has turned transporting freight from, to, and within urban areas into a major challenge. Freight transportation represents a lifeline for urban retail and industry, but causes significant negative impacts on the quality of living in urban areas in terms of congestion, emissions and space consumption. City logistics initiativ...
Conference Paper
Robotic fulfillment systems are becoming commonplace at warehouses across the world. High-density, grid-based storage systems in particular, such as the AutoStore system, are being used in a variety of contexts, but very little literature exists to guide decision makers in picking the right policies for operating such a system. Storage policies can...
Conference Paper
Liner carriers change their network on a regular basis, and they are therefore interested in a practical evaluation of the impact these changes have on the cargo flows in their networks. Despite great advancements in the practical applicability of network evaluators in recent years, vessel deployment continues to be considered as an input into the...
Article
Full-text available
Liner carriers move vessels between routes in their networks several times a year in a process called fleet repositioning. There are currently no decision support systems to allow repositioning coordinators to take advantage of recent algorithmic advances in creating repositioning plans. Furthermore, no study has addressed how to visualize repositi...
Article
Full-text available
We present a novel solution approach to the container pre-marshalling problem using the A* and IDA* algorithms combined with several novel branching and symmetry breaking rules that significantly increases the number of pre-marshalling instances that can be solved to optimality. A* and IDA* are graph search algorithms that use heuristics combined w...
Article
Container terminals around the world regularly resort the containers they store according to their retrieval times in a process called pre-marshalling, thus ensuring containers are efficiently transferred through the terminal. State-of-the-art algorithms struggle to find optimal solutions for real-world sized pre-marshalling problems. To this end,...
Conference Paper
Full-text available
The liner shipping fleet repositioning problem (LSFRP) is a central optimization problem within the container shipping industry. Several approaches exist for solving this problem using exact and heuristic techniques, however all of them use a single objective function for determining an optimal solution. We propose a multi-objective approach based...
Article
Metaheuristics have been developed to provide general purpose approaches for solving hard combinatorial problems. While these frameworks often serve as the starting point for the development of problem-specific search procedures, they very rarely work efficiently in their default state. We combine the ideas of reactive search, which adjusts key par...
Conference Paper
Full-text available
Metaheuristics have been developed to provide general purpose approaches for solving hard combinatorial problems. While these frameworks often serve as the starting point for the development of problem-specific search procedures, they very rarely work efficiently in their default state. We combine the ideas of reactive search, which adjusts key par...
Conference Paper
Container terminals across the world sort the containers in the stacks in their yard in a process called pre-marshalling to ensure their efficient retrieval for onward transport. The container pre-marshalling problem (CPMP) has mainly been considered from a deterministic perspective, with containers being assigned an exact exit time from the yard....
Conference Paper
Full-text available
Real-world instances are critical for the development of state-of-the-art algorithms, algorithm configuration techniques, and selection approaches. However , very few true industrial instances exist for most problems, which poses a problem both to algorithm designers and methods for algorithm selection. The lack of enough real data leads to an inab...
Article
The container pre-marshalling problem (CPMP) is performed at container terminals around the world to re-order containers so that they can be more efficiently transferred through the terminal. We introduce a novel decoder for a biased random-key genetic algorithm (BRKGA) that solves the CPMP. The decoder consists of a construction algorithm that lea...
Article
The cargo allocation problem is a key strategic problem that determines the profitability of a liner shipping network. We present a novel mixed-integer programming model for this problem that introduces service levels for transit time requirements and optimizes the vessel speed on each leg of a service. These extensions to the cargo allocation prob...
Conference Paper
We solve the liner shipping fleet repositioning problem (LSFRP), a key problem in the liner shipping industry, using a hybrid reactive tabu search and simulated annealing algorithm in combination with novel local search neighborhoods. Liner carriers reposition vessels between services in order to add, remove or modify services in their network. Rep...
Article
We solve a central problem in the liner shipping industry called the Liner Shipping Fleet Repositioning Problem (LSFRP). The LSFRP poses a large financial burden on liner shipping firms. During repositioning, vessels are moved between routes in a liner shipping network. Liner carriers wish to reposition vessels as cheaply as possible without disrup...
Article
Full-text available
The task of algorithm selection involves choosing an algorithm from a set of algorithms on a per-instance basis in order to exploit the varying performance of algorithms over a set of instances. The algorithm selection problem is attracting increasing attention from researchers and practitioners in AI. Years of fruitful applications in a number of...
Conference Paper
Full-text available
We present an algorithm selection benchmark based on optimal search algorithms for solving the container pre-marshalling problem (CPMP), an NP-hard problem from the field of container terminal optimization. Novel features are introduced and then systematically expanded through the recently proposed approach of latent feature analysis. The CPMP benc...
Article
Full-text available
As production and demand wax and wane across the world, liner shipping networks must be constantly adjusted due to seasonal shifts in demand and to ensure that they are compatible with the current state of the world economy. Shipping lines must add, remove and modify existing routes in their network in order to keep it relevant for their customers....
Chapter
We provide background information on several key topics for understanding the models of fleet repositioning in this monograph. Section 4.1 provides background on automated planning, a well-known technique for selecting and sequencing activities in order to achieve a set of goals. We then describe partial-order planning (POP), a specific type of aut...
Chapter
The theories of general relativity and quantum mechanics stand as two great pillars of twentieth century physics. Combing these two theories into a single frame work remains an open challenge for the twenty-first century. The synthesis of special relativity and quantum mechanics leads to quantum field theory; a framework capable of describing the i...
Chapter
Containerized shipping traces its roots back to the 1950s. We describe the origin of the standardized shipping container and how it is used in modern liner shipping networks. We further discuss the structure of such networks and describe laws and regulations regarding the formation and operation of liner shipping services.
Conference Paper
Full-text available
A particularly difficult class of scheduling and routing problems involves an objective that is a sum of time-varying action costs, which increases the size and complexity of the problem. Solve-and-improve approaches, which find an initial solution for a simplified model and improve it using a cost function, and mixed integer programming (MIP) are...
Article
A particularly difficult class of scheduling and routing problems involves an objective that is a sum of time-varying action costs, which increases the size and complexity of such problems. Solve-and-improve approaches, which find an initial solution for a simplified model and improve it using a cost function, and mixed integer programming (MIP) ar...
Conference Paper
The success or failure of a solver is oftentimes closely tied to the proper configuration of the solver’s parameters. However, tuning such parameters by hand requires expert knowledge, is time consuming, and is error-prone. In recent years, automatic algorithm configuration tools have made significant advances and can nearly always find better para...
Article
We present a novel integer programming model for analyzing inter-terminal transportation (ITT) in new and expanding sea ports. ITT is the movement of containers between terminals (sea, rail or otherwise) within a port. ITT represents a significant source of delay for containers being transshipped, which costs ports money and affects a port’s reputa...
Article
The optimization of container ship and depot operations embeds the kk-shift problem, in which containers must be stowed in stacks such that at most kk containers must be removed in order to reach containers below them. We first solve an open problem introduced by Avriel et al. (2000) by showing that changing from uncapacitated to capacitated stacks...
Conference Paper
We introduce a novel, node flow based mathematical model for the fixed-time version of a central problem in the liner shipping industry called the Liner Shipping Fleet Repositioning Problem (LSFRP). We call this version of the problem the Inflexible Visitation LSFRP (IVLSFRP). During repositioning, vessels are moved between routes in a liner shippi...
Conference Paper
Full-text available
Black-box optimization (BBO) problems arise in numerous scientific and engineering applications and are characterized by computationally intensive objective functions, which severely limit the number of evaluations that can be performed. We present a robust set of features that analyze the fitness landscape of BBO problems and show how an algorithm...
Conference Paper
Full-text available
We solve an important problem for the liner shipping industry called the Liner Shipping Fleet Repositioning Problem (LSFRP). The LSFRP poses a large financial burden on liner shipping firms. During repositioning, vessels are moved between services in a liner shipping network. Shippers wish to reposition vessels as cheaply as possible without disrup...
Article
Full-text available
The Liner Shipping Fleet Repositioning Problem (LSFRP) poses a large financial burden on liner shipping firms. During repositioning, vessels are moved between services in a liner shipping network. The LSFRP is characterized by chains of interacting activities, many of which have costs that are a function of their duration; for example, sailing slow...
Conference Paper
Full-text available
We present a new method for instance-specific algorithm configuration (ISAC). It is based on the integration of the algorithm configuration system GGA and the recently proposed stochastic off- line programming paradigm. ISAC is provided a solver with cate- gorical, ordinal, and/or continuous parameters, a training benchmark set of input instances f...
Conference Paper
Full-text available
A problem that is inherent to the development and efficient use of solvers is that of tuning parameters. The CP community has a long history of ad- dressing this task automatically. We propose a robust, inherently parallel genetic algorithm for the problem of configuring solvers automatically. In order to cope with the high costs of evaluating the...
Article
Full-text available
Fleet repositioning problems pose a high financial bur-den on shipping firms, but have received little atten-tion in the literature, despite their high importance to the shipping industry. Fleet repositioning problems are characterized by chains of interacting activities, but state-of-the-art planning and scheduling techniques do not offer cost mod...

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Projects (2)
Project
We are supporting Kevin Tierney and his group on sorting efficiently those containers waiting at bay for their ships.
Archived project