Optimisation of simultaneous train formation and car sorting at marshalling yards

Efficient and correct freight train marshalling is vital for high quality carload freight transportations. During marshalling, it is desirable that cars are sorted according to their individual drop-off locations in the outbound freight trains. Furthermore, practical limitations such as non-uniform and limited track lengths and the arrival and departure times of trains need to be considered. This paper presents a novel optimisation method for freight marshalling scheduling under these circumstances. The method is based on an integer programming formulation that is solved using column generation and branch and price. The approach minimises the number of extra shunting operations that have to be performed, and is evaluated on real-world data from the Hallsberg marshalling yard in Sweden

Acute: high-level programming language design for distributed computation

Existing languages provide good support for typeful programming of standalone programs. In a distributed system, however, there may be interaction between multiple instances of many distinct programs, sharing some (but not necessarily all) of their module structure, and with some instances rebuilt with new versions of certain modules as time goes on. In this paper we discuss programming language support for such systems, focussing on their typing and naming issues. We describe an experimental language, Acute, which extends an ML core to support distributed development, deployment, and execution, allowing type-safe interaction between separately-built programs. The main features are: (1) type-safe marshalling of arbitrary values; (2) type names that are generated (freshly and by hashing) to ensure that type equality tests suffice to protect the invariants of abstract types, across the entire distributed system; (3) expression-level names generated to ensure that name equality tests suffice for type-safety of associated values, e.g. values carried on named channels; (4) controlled dynamic rebinding of marshalled values to local resources; and (5) thunkification of threads and mutexes to support computation mobility. These features are a large part of what is needed for typeful distributed programming. They are a relatively lightweight extension of ML, should be efficiently implementable, and are expressive enough to enable a wide variety of distributed infrastructure layers to be written as simple library code above the byte-string network and persistent store APIs. This disentangles the language runtime from communication intricacies. This paper highlights the main design choices in Acute. It is supported by a full language definition (of typing, compilation, and operational semantics), by a prototype implementation, and by example distribution libraries

A formal semantics for control and data flow in the gannet service-based system-on-chip architecture

There is a growing demand for solutions which allow the design of large and complex reconfigurable Systems-on- Chip (SoC) at high abstraction levels. The Gannet project proposes a functional programming approach for high-abstraction design of very large SoCs. Gannet is a distributed service-based SoC architecture, i.e. a network of services offered by hardware or software cores. The Gannet SoC is task-level reconfigurable: it performs tasks by executing functional task description programs using a demand-driven dataflow mechanism. The Gannet architecture combines the flexible connectivity offered by a Networkon- Chip with the functional language paradigm to create a fully concurrent distributed SoC with the option to completely separate data flows from control flows. This feature is essential to avoid a bottleneck at he controller for run-time control of multiple high-throughput data flows. In this paper we present the Gannet architecture and language and introduce an operational semantics to formally describe the mechanism to separate control and data flows

Solving the unit-load pre-marshalling problem in block stacking storage systems with multiple access directions

Block stacking storage systems are highly adaptable warehouse systems with low investment costs. With multiple, deep lanes they can achieve high storage densities, but accessing some unit loads can be time-consuming. The unit-load pre-marshalling problem sorts the unit loads in a block stacking storage system in off-peak time periods to prepare for upcoming orders. The goal is to find a minimum number of unit-load moves needed to sequence a storage bay in ascending order based on the retrieval priority group of each unit load. In this paper, we present two solution approaches for determining the minimum number of unit-load moves. We show that for storage bays with one access direction, it is possible to adapt existing, optimal tree search procedures and lower bound heuristics from the container pre-marshalling problem. For multiple access directions, we develop a novel, two-step solution approach based on a network flow model and an A* algorithm with an adapted lower bound that is applicable in all scenarios. We further analyze the performance of the presented solutions in computational experiments for randomly generated problem instances and show that multiple access directions greatly reduce both the total access time of unit loads and the required sorting effort

ASlib: A Benchmark Library for Algorithm Selection

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 domains have resulted in a large amount of data, but the community lacks a standard format or repository for this data. This situation makes it difficult to share and compare different approaches effectively, as is done in other, more established fields. It also unnecessarily hinders new researchers who want to work in this area. To address this problem, we introduce a standardized format for representing algorithm selection scenarios and a repository that contains a growing number of data sets from the literature. Our format has been designed to be able to express a wide variety of different scenarios. Demonstrating the breadth and power of our platform, we describe a set of example experiments that build and evaluate algorithm selection models through a common interface. The results display the potential of algorithm selection to achieve significant performance improvements across a broad range of problems and algorithms.Comment: Accepted to be published in Artificial Intelligence Journa

Cadence and Formal Function in Mendelssohn's Sonata Forms

Mendelssohn’s sonata-form practices owe much to classical syntactic paradigms, but his music testifies to the growing trend in the nineteenth century for novel methods of syntactic organisation. He engages methods of syntactic proliferation, functional expansion and extension, truncation, compression, and deletion, which engenders a phrase-structural complexity and a multi-layered thematic syntax. In so doing, Mendelssohn makes cadences and structural support subservient to a continuous, proliferative agenda, and capitalises on the capacity for cadential deferral, and delayed consolidation of the tonic. Despite marshalling seemingly coherent, conventional intrathematic units, Mendelssohn’s radical treatment therein undermines clear interthematic groupings, engaging a continuous reorientation of functionality. As a point of departure from classical precedents, reconsideration of the interdependence between cadence and closure is evidently necessary. This study contributes to recent scholarly momentum in nineteenth-century music and in Mendelssohn studies by addressing formal articulation in the context of Mendelssohn’s novel approach to syntax, in order to illuminate his continued process of downplaying, deferring, and deleting cadences, and the issues of long-range teleology, functional instability, and interthematic indeterminateness that result from these processes

The TASTE Toolset: turning human designed heterogeneous systems into computer built homogeneous software.

The TASTE tool-set results from spin-off studies of the ASSERT project, which started in 2004 with the objective to propose innovative and pragmatic solutions to develop real-time software. One of the primary targets was satellite flight software, but it appeared quickly that their characteristics were shared among various embedded systems. The solutions that we developed now comprise a process and several tools ; the development process is based on the idea that real-time, embedded systems are heterogeneous by nature and that a unique UML-like language was not helping neither their construction, nor their validation. Rather than inventing yet another "ultimate" language, TASTE makes the link between existing and mature technologies such as Simulink, SDL, ASN.1, C, Ada, and generates complete, homogeneous software-based systems that one can straightforwardly download and execute on a physical target. Our current prototype is moving toward a marketed product, and sequel studies are already in place to support, among others, FPGA systems