Fast generalized cross validation using Krylov subspace methods

The task of fitting smoothing spline surfaces to meteorological data such as temperature or rainfall observations is computationally intensive. The generalized cross validation (GCV) smoothing algorithm, if implemented using direct matrix techniques, is O(n ³) computationally, and memory requirements are O(n ²). Thus, for data sets larger than a few hundred observations, the algorithm is prohibitively slow. The core of the algorithm consists of solving series of shifted linear systems, and iterative techniques have been used to lower the computational complexity and facilitate implementation on a variety of supercomputer architectures. For large data sets though, the execution time is still quite high. In this paper we describe a Lanczos based approach that avoids explicitly solving the linear systems and dramatically reduces the amount of time required to fit surfaces to sets of data.      

Critical path analysis and resource constrained project scheduling — Theory and practice

Critical path techniques have been in documented use since the mid 1950's and are now widely used in most aspects of project planning and control. Interest in this area in recent years has been mainly concerned with making the best use of scarce resources throughout the duration of a project and a considerable amount of work has been undertaken in this area by both theorists and practitioners in project management. There is still however an apparent gap between the published theoretical work and the requirements of project schedulers and managers in the field and this paper briefly describes the different approaches taken, how they differ and suggests where future effort may be directed.     

Evaluating environmental performance using statistical process control techniques

This paper builds on recent work on measuring and evaluating environmental performance of a process using statistical process control (SPC) techniques. We propose the CUSUM chart as a tool to monitor emissions data so that abnormal changes can be detected in a timely manner, and we propose using process capability indices to evaluate environmental performance in terms of the risk of non-compliance situations arising. In doing so, the paper fills an important gap in the ISO 14000 and TQEM literatures, which have focused more on environmental management systems and qualitative aspects rather than on quantitative tools. We explore how process capability indices have the potential to be useful as a risk management tool for practitioners and to help regulators execute and prioritize their enforcement efforts. Together, this should help in setting up useful guidelines for evaluating actual environmental performance against the firm's environmental objectives and targets and regulatory requirements, as well as encouraging further development and application of SPC techniques to the field of environmental quality management and data analysis.     

Mathematical Programming Modelling Using MGG

MGG is a software package for the application of mathematicalprogramming (MP). It complements the Sciconic MP code by providinga facility for developing MP models quickly and efficiently,and it enables changes to be made easily to established models.It is available on a wide range of minis and mainframes anda version of it is available as part of the Micro LP systemon IBM PCs and compatibles. MGG is based on an approach to modellingMP problems which stresses the primacy of the mathematical formulation.The process of MP modelling is divided into two stages: modelpreparation and running of the model. The user writes a mathematicalformulation, which MGG converts to matrix generator and reportwriter programs. This is done once to produce the programs whichcan then be run many times on different data. This paper describesMGG and draws comparisons with other matrix generator and mathematicalprogramming languages. It starts by considering how an MP problemcan be described, and then sets out a methodology for formulation.The MGG language is based upon this approach. A simple exampleis presented which is shown both as an algebraic formulationand in the MGG language. The process of building and runningmodels with MGG is then described. Finally, some comments areoffered on experience of using the software.     

Comparing constraint programming and mathematical programming approaches to discrete optimisation—the change problem

This paper is aimed at researchers and practitioners in Operational Research who are interested in the new field of Constraint Programming/Constraint Logic Programming. Due to differing terminology and problem representation they might have found it difficult to access the field. The paper focuses on discrete optimisation problems. The first part lists frequently used terms in Constraint Programming (CP), contrasting them with their counterparts in Mathematical Programming (MP). The second part explains some of the most important concepts and techniques in more detail by comparing the CP and MP implementations of a small example problem, the ‘Change Problem’. It includes an overview of the respective results. In conclusion a more generalised comparison of CP and MP techniques is given.     

Three steps multiobjective decision process for software release planning

This paper deals with how to determine which features should be included in the software to be developed. Metaheuristic techniques have been applied to this problem and can help software developers when they face contradictory goals. We show how the knowledge and experience of human experts can be enriched by these techniques, with the idea of obtaining a better requirements selection than that produced by expert judgment alone. This objective is achieved by embedding metaheuristics techniques into a requirements management tool that takes advantage of them during the execution of the development stages of any software development project. © 2015 Wiley Periodicals, Inc. Complexity 21: 250–262, 2016     

Better management of blood supply-chain with GIS-based analytics

This paper presents a novel application of operations research, data mining and geographic information-systems-based analytics to support decision making in blood supply chain management. This, blood reserve availability assessment, tracking, and management system (BRAMS), research project has been funded by the Office of the Secretary of Defense. (This DoD funded SBIR project is performed by the researchers at Knowledge Based Systems, Inc. (KBSI).) The rapidly increasing demand, criticality of the product, strict storage and handling requirements, and the vastness of the theater of operations, make blood supply-chain management a complex, yet vital problem for the department of defense. In order to address this problem a variety of contemporary analytic techniques are used to analyze inventory and consumption patterns, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The current implementation of the system is being actively used by 130 mangers at different levels in the supply chain including facilities at Osan Air Force Base in South Korea and Incirlik Air Force Base in Turkey.