The Art of Knowledge Exchange: A Results-Focused Planning Guide for Development Practitioners

Designing and implementing knowledge exchange initiatives can be a big undertaking. This guide takes the guesswork out of the process by breaking it down into simple steps and providing tools to help you play a more effective role as knowledge connector and learning facilitator

Manufacturing Processes Management with Usage of Simulation Tools

Simulace výrobních procesů pomáhá optimalizovat výrobu, logistiku a další systémy, díky čemuž dochází ke snižování nákladů a racionalizaci vnitropodnikových procesů. Využitím diskrétní simulace programu Witness Power with Ease se v diplomové práci optimalizuje logistický tok materiálu ve společnosti Hella Autotechnik, s.r.o. Práce přibližuje metody a jednotlivé fáze tvorby modelu včetně jeho validace a navrhuje vylepšení, díky kterému by mělo dojít ke snížení nákladů na dopravní služby o 24 400 Kč měsíčně.By optimizing the logistics, production and other systems the simulation can reduce costs and rationalise business processes. By use of discrete simulation in software Witness Power with Ease is in this diploma thesis optimised logistical flow of material in the company Hella Autotechnik, s.r.o. The thesis introduces methods and particular phases of creating the model including its validation. The proposal in the diploma work suggests the improvement to lower the costs for the transportation services by 24,400 CZK per month.

You Cannot Have Your Cake and Eat It, too: How Induced Goal Conflicts Affect Complex Problem Solving

Managing multiple and conflicting goals is a demand typical to both everyday life and complex coordination tasks. Two experiments (N = 111) investigated how goal conflicts affect motivation and cognition in a complex problem- solving paradigm. In Experiment 1, participants dealt with a game-like computer simulation involving a predefined goal relation: Parallel goals were independent, mutually facilitating, or interfering with one another. As expected, goal conflicts entailed lowered motivation and wellbeing. Participants’ understanding of causal effects within the simulation was im- paired, too. Behavioral measures of subjects’ interventions support the idea of adaptive, self-regulatory processes: reduced action with growing awareness of the goal conflict and balanced goal pursuit. Experiment 2 endorses the hypotheses of motivation loss and reduced acquisition of system-related knowledge in an extended problem-solving paradigm of four conflicting goals. Impairing effects of goal interference on motivation and wellbeing were found, although less distinct and robust as in Experiment 1. Participants undertook fewer interventions in case of a goal conflict and acquired less knowledge about the system. Formal complexity due to the interconnectedness among goals is discussed as a limiting influence on inferring the problem structure

Blowing Open the Bottleneck: Designing New Approaches to Increase Nurse Education Capacity

Outlines the challenges of expanding the nurse education capacity to meet nursing shortages. Explores strategies such as partnerships among stakeholders, faculty development, revised curricula, and policy and regulatory advocacy, and offers case studies

Statistical QoS Analysis of Full Duplex and Half Duplex Heterogeneous Cellular Networks

In this paper, statistical Quality of Service provisioning in next generation heterogeneous mobile cellular networks is investigated. To this aim, any active entity of the cellular network is regarded as a queuing system, whose statistical QoS requirements depend on the specific application. In this context, by quantifying the performance in terms of effective capacity, we introduce a lower bound for the system performance that facilitates an efficient analysis. We exploit this analytical framework to give insights about the possible improvement of the statistical QoS experienced by the users if the current heterogeneous cellular network architecture migrates from a Half Duplex to a Full Duplex mode of operation. Numerical results and analysis are provided, where the network is modeled as a Mat\'ern point processes with a hard core distance. The results demonstrate the accuracy and computational efficiency of the proposed scheme, especially in large scale wireless systems

Optimisation of stochastic networks with blocking: a functional-form approach

This paper introduces a class of stochastic networks with blocking, motivated by applications arising in cellular network planning, mobile cloud computing, and spare parts supply chains. Blocking results in lost revenue due to customers or jobs being permanently removed from the system. We are interested in striking a balance between mitigating blocking by increasing service capacity, and maintaining low costs for service capacity. This problem is further complicated by the stochastic nature of the system. Owing to the complexity of the system there are no analytical results available that formulate and solve the relevant optimization problem in closed form. Traditional simulation-based methods may work well for small instances, but the associated computational costs are prohibitive for networks of realistic size. We propose a hybrid functional-form based approach for finding the optimal resource allocation, combining the speed of an analytical approach with the accuracy of simulation-based optimisation. The key insight is to replace the computationally expensive gradient estimation in simulation optimisation with a closed-form analytical approximation that is calibrated using a single simulation run. We develop two implementations of this approach and conduct extensive computational experiments on complex examples to show that it is capable of substantially improving system performance. We also provide evidence that our approach has substantially lower computational costs compared to stochastic approximation

Agent-based transportation planning compared with scheduling heuristics

Here we consider the problem of dynamically assigning vehicles to transportation orders that have di¤erent time windows and should be handled in real time. We introduce a new agent-based system for the planning and scheduling of these transportation networks. Intelligent vehicle agents schedule their own routes. They interact with job agents, who strive for minimum transportation costs, using a Vickrey auction for each incoming order. We use simulation to compare the on-time delivery percentage and the vehicle utilization of an agent-based planning system to a traditional system based on OR heuristics (look-ahead rules, serial scheduling). Numerical experiments show that a properly designed multi-agent system may perform as good as or even better than traditional methods