Stefan Voß

Container terminal operation and operations research — a classification and literature review

In the last four decades the container as an essential part of a unit-load-concept has achieved undoubted importance in international sea freight transportation. With ever increasing containerization the number of seaport container terminals and competition among them have become quite remarkable. Operations are nowadays unthinkable without effective and efficient use of information technology as well as appropriate optimization (operations research) methods. In this paper we describe and classify the main logistics processes and operations in container terminals and present a survey of methods for their optimization.

Operations research at container terminals: a literature update

The current decade sees a considerable growth in worldwide container transportation and with it an indispensable need for optimization. Also the interest in and availability of academic literatures as well as case reports are almost exploding. With this paper an earlier survey which proved to be of utmost importance for the community is updated and extended to provide the current state of the art in container terminal operations and operations research.

Solving the continuous flow-shop scheduling problem by metaheuristics

Abstract Continuous flow-shop scheduling problems circumscribe an important class of sequencing problems in the field of production planning. The problem considered here is to find a permutation of jobs to be processed sequentially on a number of machines under the restriction that the processing of each job has to be continuous with respect to the objective of minimizing the total processing time (flow-time). This problem is NP -hard. We consider the application of different kinds of metaheuristics from a practical point of view, examining the trade-off between running time and solution quality as well as the knowledge and efforts needed to implement and calibrate the algorithms. Computational results show that high quality results can be obtained in an efficient way by applying metaheuristics software components with neither the need to understand their inner working nor the necessity to manually tune parameters.

Steiner's problem in graphs: heuristic methods

Abstract Real world problems arising in the layout of connection structures in networks as e.g. in VLSI design may often be decomposed into a number of well-known combinatorial optimization problems. Steiners problem in graphs is included within this context. According to its complexity one is interested in developing efficient heuristic algorithms to find good approximate solutions. Here a comparison of various heuristic methods for Steiners problem in graphs is presented.

Simple assembly line balancing—Heuristic approaches

In this paper heuristics for Type 1 and Type 2 of the Simple Assembly Line Balancing Problem (SALBP) are described. Type 1 of SALBP (SALBP-1) consists of assigning tasks to work stations such that the number of stations is minimized for a given production rate whereas Type 2 (SALBP-2) is to maximize the production rate, or equivalently, to minimize the sum of idle times for a given number of stations. In both problem types, precedence constraints between the tasks have to be considered.We describe bidirectional and dynamic extensions to heuristic priority rules widely used for SALBP-1. For the solution of SALBP-2 we present search methods which involve the repetitive application of procedures for SALBP-1. Furthermore, improvement procedures for SALBP-2 are developed and combined with tabu search, a recent strategy to overcome local optimality. Several optional elements of tabu search are discussed. Finally, the application of a nontraditional tabu search approach to solve SALBP-1 is investigated. Computational experiments validate the effectiveness of our new approaches.

Dynamic tabu list management using the reverse elimination method

Tabu search is a metastrategy for guiding known heuristics to overcome local optimality. Successful applications of this kind of metaheuristic to a great variety of problems have been reported in the literature. However, up to now mainly static tabu list management ideas have been applied. In this paper we describe a dynamic strategy, the reverse elimination method, and give directions on improving its computational effort. The impact of the method will be shown with respect to a multiconstraint version of the zero-one knapsack problem. Numerical results are presented comparing it with a simulated annealing approach.

Optimization Software Class Libraries

Many decision problems in business and engineering may be formulated as optimization problems. Optimization problems in practice are diverse, often complex and evolve over time, so one requires both ready-to-use optimization software packages and optimization software libraries, which provide more or less adaptable building blocks for application-specific software systems.

SteinLib: An Updated Library on Steiner Tree Problems in Graphs

In this paper we present the SteinLib, a library of data sets for the Steiner tree problem in graphs. This library extends former libraries on Steiner tree problems by many new interesting and difficult instances, most of them arising from real-world applications. We give a survey on the difficulty of these problem instances by stating references to state-of-the-art software packages that were the first or are currently among the best to solve these instances.

A mathematical formulation and complexity considerations for the blocks relocation problem

The blocks relocation problem (BRP) may be defined as follows: given a set of homogeneous blocks stored in a two-dimensional stock, which relocations are necessary to retrieve the blocks from the stock in a predefined order while minimizing the number of those relocations? In this paper, we first prove NP-hardness of the BRP as well as a special case, closing open research questions. Moreover, we propose different solution approaches. First, a mathematical model is presented that provides optimal solutions to the general BRP in cases where instances are small. To overcome such limitation, some realistic assumption taken from the literature is introduced, leading to the definition of a binary linear programming model. In terms of computational time, this approach is reasonably fast to be used to solve medium-sized instances. In addition, we propose a simple heuristic based upon a set of relocation rules. This heuristic is used to generate “good” quality solutions for larger instances in very short computational time, and, consequently, is proposed for tackling problem instances where solutions are required (almost) immediately. Solution quality of the heuristic is measured against optimal solutions obtained using a state-of-the-art commercial solver and both of them are compared with reference results from literature.

A classification of formulations for the (time-dependent) traveling salesman problem

Abstract The time-dependent traveling salesman problem (TDTSP) is a generalization of the classical traveling salesman problem where the cost of any given arc is dependent of its position in the tour. The TDTSP can model several real world applications (e.g., one-machine sequencing). In this paper we present a classification of formulations for the TDTSP. This framework includes both new and old formulations. The new formulation presented in this paper is derived from a quadratic assignment model for the TDTSP. In a first step, Lawlers transformation procedure is used to derive an equivalent linearized version of the quadratic model. In a second step, a stronger formulation is obtained by tightening some constraints of the previous formulation. It is shown that, in terms of linear relaxations, the latter formulation is either equivalent or better than other formulations already known from the literature. Finally, we compare these formulations with other well known formulations for the classical traveling salesman problem.