Optimal Reservoir Operation for Flood Control Using Folded Dynamic Programming

Folded Dynamic Programming (FDP) is adopted for developing optimalnreservoir operation policies for flood control. It is applied to a case study of Hirakud Reservoir in Mahanadi basin, India with the objective of deriving optimal policy for flood control. The river flows down to Naraj, the head of delta where a major city is located and finally joins the Bay of Bengal. As Hirakud reservoir is on the upstream side of delta area in the basin, it plays an important role in alleviating the severity of the flood for this area. Data of 68 floods such as peaks of inflow hydrograph, peak of outflow from reservoir during each flood, peak of flow hydrograph at Naraj and d/s catchment contribution are utilized. The combinations of 51, 54, 57 thousand cumecs as peak inflow into reservoir and 25.5, 20, 14 thousand cumecs respectively as,peak d/s catchment contribution form the critical combinations for flood situation. It is observed that the combination of 57 thousand cumecs of inflow into reservoir and 14 thousand cumecs for d/s catchment contribution is the most critical among the critical combinations of flow series. The method proposed can be extended to similar situations for deriving reservoir operating policies for flood control.

A new constraint programming approach for optimising a coal rail system

Because of the bottlenecking operations in a complex coal rail system, millions of dollars are costed by mining companies. To handle this issue, this paper investigates a real-world coal rail system and aims to optimise the coal railing operations under constraints of limited resources (e.g., limited number of locomotives and wagons). In the literature, most studies considered the train scheduling problem on a single-track railway network to be strongly NP-hard and thus developed metaheuristics as the main solution methods. In this paper, a new mathematical programming model is formulated and coded by optimization programming language based on a constraint programming (CP) approach. A new depth-first-search technique is developed and embedded inside the CP model to obtain the optimised coal railing timetable efficiently. Computational experiments demonstrate that high-quality solutions are obtainable in industry-scale applications. To provide insightful decisions, sensitivity analysis is conducted in terms of different scenarios and specific criteria. Keywords Train scheduling · Rail transportation · Coal mining · Constraint programming

Safeguarding against new privacy threats in inter-enterprise collaboration environments

Inter-enterprise collaboration has become essential for the success of enterprises. As competition increasingly takes place between supply chains and networks of enterprises, there is a strategic business need to participate in multiple collaborations simultaneously. Collaborations based on an open market of autonomous actors set special requirements for computing facilities supporting the setup and management of these business networks of enterprises. Currently, the safeguards against privacy threats in collaborations crossing organizational borders are both insufficient and incompatible to the open market. A broader understanding is needed of the architecture of defense structures, and privacy threats must be detected not only on the level of a private person or enterprise, but on the community and ecosystem levels as well. Control measures must be automated wherever possible in order to keep the cost and effort of collaboration management reasonable. This article contributes to the understanding of the modern inter-enterprise collaboration environment and privacy threats in it, and presents the automated control measures required to ensure that actors in inter-enterprise collaborations behave correctly to preserve privacy.

Bullying and organisational politics in competitive and rapidly changing work environments

This paper argues that workplace bullying can in some cases be a form of organisational politics, that is, a deliberate, competitive strategy from the perspective of the individual perpetrator. A cross-sectional study conducted among business professionals revealed that there was a correlation between a politicised and competitive climate and bullying. This finding implies that globalisation, increased pressures for efficiency, and restructuring, which limits the number of management positions and thereby contributes to increased internal competition, may lead to more bullying. The findings have important implications for management, since the possible political aspects of bullying must be taken into account in order to be able to undertake successful prevention and intervention measures.

Dynamic programming based optimum non-uniform samples for speech reconstruction and coding

Non-uniform sampling of a signal is formulated as an optimization problem which minimizes the reconstruction signal error. Dynamic programming (DP) has been used to solve this problem efficiently for a finite duration signal. Further, the optimum samples are quantized to realize a speech coder. The quantizer and the DP based optimum search for non-uniform samples (DP-NUS) can be combined in a closed-loop manner, which provides distinct advantage over the open-loop formulation. The DP-NUS formulation provides a useful control over the trade-off between bitrate and performance (reconstruction error). It is shown that 5-10 dB SNR improvement is possible using DP-NUS compared to extrema sampling approach. In addition, the close-loop DP-NUS gives a 4-5 dB improvement in reconstruction error.

A generalized Linear Programming based approach to optimal divisible load scheduling

In this paper we propose a general Linear Programming (LP) based formulation and solution methodology for obtaining optimal solution to the load distribution problem in divisible load scheduling. We exploit the power of the versatile LP formulation to propose algorithms that yield exact solutions to several very general load distribution problems for which either no solutions or only heuristic solutions were available. We consider both star (single-level tree) networks and linear daisy chain networks, having processors equipped with front-ends, that form the generic models for several important network topologies. We consider arbitrary processing node availability or release times and general models for communication delays and computation time that account for constant overheads such as start up times in communication and computation. The optimality of the LP based algorithms is proved rigorously.

Second order cone programming approaches for handling missing and uncertain data

We propose a novel second order cone programming formulation for designing robust classifiers which can handle uncertainty in observations. Similar formulations are also derived for designing regression functions which are robust to uncertainties in the regression setting. The proposed formulations are independent of the underlying distribution, requiring only the existence of second order moments. These formulations are then specialized to the case of missing values in observations for both classification and regression problems. Experiments show that the proposed formulations outperform imputation.

PROMIDS: A PROtotype multi-rIng data flow system for functional programming languages

This paper presents a detailed description of the hardware design and implementation of PROMIDS: a PROtotype Multi-rIng Data flow System for functional programming languages. The hardware constraints and the design trade-offs are discussed. The design of the functional units is described in detail. Finally, we report our experience with PROMIDS.

A mathematical programming approach to optimal Markovian switching of Poisson arrival streams to queueing systems

Motivated by certain situations in manufacturing systems and communication networks, we look into the problem of maximizing the profit in a queueing system with linear reward and cost structure and having a choice of selecting the streams of Poisson arrivals according to an independent Markov chain. We view the system as a MMPP/GI/1 queue and seek to maximize the profits by optimally choosing the stationary probabilities of the modulating Markov chain. We consider two formulations of the optimization problem. The first one (which we call the PUT problem) seeks to maximize the profit per unit time whereas the second one considers the maximization of the profit per accepted customer (the PAC problem). In each of these formulations, we explore three separate problems. In the first one, the constraints come from bounding the utilization of an infinite capacity server; in the second one the constraints arise from bounding the mean queue length of the same queue; and in the third one the finite capacity of the buffer reflect as a set of constraints. In the problems bounding the utilization factor of the queue, the solutions are given by essentially linear programs, while the problems with mean queue length constraints are linear programs if the service is exponentially distributed. The problems modeling the finite capacity queue are non-convex programs for which global maxima can be found. There is a rich relationship between the solutions of the PUT and PAC problems. In particular, the PUT solutions always make the server work at a utilization factor that is no less than that of the PAC solutions.

Nonlinear programming solutions for controlling the vibration pattern of stretched strings

The problem of controlling the vibration pattern of a driven string is considered. The basic question dealt with here is to find the control forces which reduce the energy of vibration of a driven string over a prescribed portion of its length while maintaining the energy outside that length above a desired value. The criterion of keeping the response outside the region of energy reduction as close to the original response as possible is introduced as an additional constraint. The slack unconstrained minimization technique (SLUMT) has been successfully applied to solve the above problem. The effect of varying the phase of the control forces (which results in a six-variable control problem) is then studied. The nonlinear programming techniques which have been effectively used to handle problems involving many variables and constraints therefore offer a powerful tool for the solution of vibration control problems.

Psychologically-Based and Content-Oriented Experience in Entertainment Virtual Environments

In daily life, rich experiences evolve in every environmental and social interaction. Because experience has a strong impact on how people behave, scholars in different fields are interested in understanding what constitutes an experience. Yet even if interest in conscious experience is on the increase, there is no consensus on how such experience should be studied. Whatever approach is taken, the subjective and psychologically multidimensional nature of experience should be respected. This study endeavours to understand and evaluate conscious experiences. First I intro-duce a theoretical approach to psychologically-based and content-oriented experience. In the experiential cycle presented here, classical psychology and orienting-environmental content are connected. This generic approach is applicable to any human-environment interaction. Here I apply the approach to entertainment virtual environments (VEs) such as digital games and develop a framework with the potential for studying experiences in VEs. The development of the methodological framework included subjective and objective data from experiences in the Cave Automatic Virtual Environment (CAVE) and with numerous digital games (N=2,414). The final framework consisted of fifteen factor-analytically formed subcomponents of the sense of presence, involvement and flow. Together, these show the multidimensional experiential profile of VEs. The results present general experiential laws of VEs and show that the interface of a VE is related to (physical) presence, which psychologically means attention, perception and the cognitively evaluated realness and spatiality of the VE. The narrative of the VE elicits (social) presence and involvement and affects emotional outcomes. Psychologically, these outcomes are related to social cognition, motivation and emotion. The mechanics of a VE affect the cognitive evaluations and emotional outcomes related to flow. In addition, at the very least, user background, prior experience and use context affect the experiential variation. VEs are part of many peoples lives and many different outcomes are related to them, such as enjoyment, learning and addiction, depending on who is making the evalua-tion. This makes VEs societally important and psychologically fruitful to study. The approach and framework presented here contribute to our understanding of experiences in general and VEs in particular. The research can provide VE developers with a state-of-the art method (www.eveqgp.fi) that can be utilized whenever new product and service concepts are designed, prototyped and tested.

Ordered Ports – a Language Concept for High-level Distributed Programming

A new language concept for high-level distributed programming is proposed. Programs are organised as a collection of concurrently executing processes. Some of these processes, referred to as liaison processes, have a monitor-like structure and contain ports which may be invoked by other processes for the purposes of synchronisation and communication. Synchronisation is achieved by conditional activation of ports and also through port control constructs which may directly specify the execution ordering of ports. These constructs implement a path-expression-like mechanism for synchronisation and are also equipped with options to provide conditional, non-deterministic and priority ordering of ports. The usefulness and expressive power of the proposed concepts are illustrated through solutions of several representative programming problems. Some implementation issues are also considered.