Comparison between Two Policy Strategies for Scheduling in a Biomass Logistic System

Comparison between two policy strategies for scheduling trucks in a biomass logistic system

The objective of this paper is to demonstrate how calculations of greenhouse gas emissions from transport in logistics systems can be analysed with Discrete Event Simulation models. For this, modelling was performed by considering the discrete aspects associated with transport systems with the continuous component of the carbon monoxide emissions from the fleet. The simulation models were constructed with the free and open-source software Ururau. The simulations searched to compare trade-offs of economic and environmental variables, in contrast to what is usually done in these types of systems, such as comparing economic variables with inventory variables. The results indicated that there is no direct relationship of proportionality between, for example, the delivery time and the total emissions produced by trucks.

CHAPTER X - DISCRETE EVENT SIMULATION PROGRAMMING

This paper presents a discrete event simulation model to help improving healthcare service provided by an emergency department at a private hospital at Zagazig, Egypt. We construct a patient flow division model by dividing patients according to their severity level. Although patients division and routing have significant evidence in improving health service in terms of waiting times and Length of Stay (LoS), there is a lack in a detailed system evaluation and implementation under this configuration. Based on system observation and health care provider’s interviews, a comprehensive and clear picture of the system has been drawn along with a conceptual model showing different patient flows through the studied system. A discrete event simulation model of the Emergency Department is built using collected data. Different operational scenarios were tested against the baseline scenario to study the impact of patient flow division, including different staff capacities and different patient magnitudes. Results indicate that waiting times and length of patient stay can be significantly improved under the proposed system configuration.

GWorkS – A discrete event simulation model on crop handling processes in a mobile rose cultivation system

Schizophrenia is a chronic disease characterized by periods of relative stability interrupted by acute episodes (or relapses). The course of the disease may vary considerably between patients. Patient histories show considerable inter- and even intra-individual variability. We provide a critical assessment of the advantages and disadvantages of three modelling techniques that have been used in schizophrenia: decision trees, (cohort and micro-simulation) Markov models and discrete event simulation models. These modelling techniques are compared in terms of building time, data requirements, medico-scientific experience, simulation time, clinical representation, and their ability to deal with patient heterogeneity, the timing of events, prior events, patient interaction, interaction between co-variates and variability (first-order uncertainty). We note that, depending on the research question, the optimal modelling approach should be selected based on the expected differences between the comparators, the number of co-variates, the number of patient subgroups, the interactions between co-variates, and simulation time. Finally, it is argued that in case micro-simulation is required for the cost-effectiveness analysis of schizophrenia treatments, a discrete event simulation model is best suited to accurately capture all of the relevant interdependencies in this chronic, highly heterogeneous disease with limited long-term follow-up data.

Goal Directed Perfusion (Gdp): A Differential Cost Analysis In Uk And Us.

BackgroundThe World Health Organization (WHO) has called for the elimination of cervical cancer. Unfortunately, the implementation of cost-effective prevention and control strategies has faced significant barriers, such as insufficient guidance on best practices for resource and operations planning. Therefore, we demonstrate the value of discrete event simulation (DES) in implementation science research and practice, particularly to support the programmatic and operational planning for sustainable and resilient delivery of healthcare interventions. Our specific example shows how DES models can inform planning for scale-up and resilient operations of a new HPV-based screen and treat program in Iquitos, an Amazonian city of Peru.MethodsUsing data from a time and motion study and cervical cancer screening registry from Iquitos, Peru, we developed a DES model to conduct virtual experimentation with “what-if” scenarios that compare different workflow and processing strategies under resource constraints and disruptions to the screening system.ResultsOur simulations show how much the screening system’s capacity can be increased at current resource levels, how much variability in service times can be tolerated, and the extent of resilience to disruptions such as curtailed resources. The simulations also identify the resources that would be required to scale up for larger target populations or increased resilience to disruptions, illustrating the key tradeoff between resilience and efficiency. Thus, our results demonstrate how DES models can inform specific resourcing decisions but can also highlight important tradeoffs and suggest general “rules” for resource and operational planning.ConclusionsMultilevel planning and implementation challenges are not unique to sustainable adoption of cervical cancer screening programs but represent common barriers to the successful scale-up of many preventative health interventions worldwide. DES represents a broadly applicable tool to address complex implementation challenges identified at the national, regional, and local levels across settings and health interventions—how to make effective and efficient operational and resourcing decisions to support program adaptation to local constraints and demands so that they are resilient to changing demands and more likely to be maintained with fidelity over time.

There are several techniques for estimating cost and time for development. These are known in engineering as software metrics. LOC (lines of code), COCOMO (COnstructive COst Model), and FPA (Function Point Analysis) are examples of such techniques. Although Discrete Event Simulation Modeling (DESM) has some differences from classical development, it is possible to draw a parallel between these techniques and DESM. This article reviews some of the metrics from engineering, and, based on those, proposes a metric for estimating time for the implementation of a simulation model using one specific simulation software. The results obtained for 22 real simulation projects showed that the proposed technique can estimate the time for development with acceptable accuracy (average error of 6% and maximum absolute error of 38%) for models that have less that 200 simulation objects.

Introduction. Lately the ability to ship products on time and without damage has more priorities than a good price. This redistribution of emphasis on the market has led to the development of logistics management. The purpose of the paper is to take a look at the transport and logistics system of Ukraine, find its main problems and tasks. Results. Ukraine's place in the global transportation network can be determined by the LPI Logistics Efficiency Index provided by the World Bank. Transport infrastructure is very important for the economic and social development of the country. A structured logistics system is important for efficient international trade as it involves long-distance transportation. Ukraine's internal transport and logistics system has many problems. This is due to the lack of the necessary transport and road complex. Ukrainian entrepreneurs hardly use information systems in their activities, such as SRM (supplier relationship management). It can be explained with different reasons: distrust of new technologies; high cost of information systems; lack of understanding of the importance of using modern technologies. Lately there has been an increase in the cost of transport and logistics. The logistics system of domestic enterprises faces the following tasks: management and regulation of material flow; organization of the transport process and inventory management of the enterprise. Conclusion. Ukraine's transport and logistics system is still under development, with many problems that need to be solved. Particular attention should be paid to improving the quality of transport services both within the country and abroad to strengthen Ukraine's position in the international market. In further research it is recommended to help entrepreneurs learn more about information systems because it`s an important part of the development of transport and logistics chains.

The physical Internet (PI) is a conceptual, innovative, and contemporary modular distribution logistics system that has garnered the interest of both researchers and practitioners as an alternative to conventional logistics. It aims to be more environmentally friendly, more socially responsible, and also more profitable. The key concept behind the PI logistics system is the routing of highly modular containers through transit centers (called PI hubs) to obtain a very efficient transport network that exploits consolidation opportunities. A systems model of the traditional and PI networks is developed as an aggregation of optimal point-to-point dispatch models between pairs of cities. This is then used to characterize the behavior of the traditional and PI logistics systems for several different logistics system key performance indicators. Based on the modeling assumptions in this paper, it is concluded that the benefits of the PI are in reducing the inventory cost and the total logistics system cost. However, a fewer truck trips are required in the traditional system, which also has a lower total order delivery time. While the transportation cost in the PI and traditional systems are comparable, the total cost of the PI system is significantly lower.

This paper presents the results of a simulation using physical objects. This concept integrates the physical dimensions of an entity such as length, width, and weight, with the usual process flow paradigm, recurrent in the discrete event simulation models. Based on a naval logistics system, we applied this technique in an access channel of the largest port of Latin America. This system is composed by vessel movement constrained by the access channel dimensions. Vessel length and width dictates whether it is safe or not to have one or two ships simultaneously. The success delivered by the methodology proposed was an accurate validation of the model, approximately 0.45% of deviation, when compared to real data. Additionally, the model supported the design of new terminals operations for Santos, delivering KPIs such as: canal utilization, queue time, berth utilization, and throughput capability.

Due to economic changes and population growth, the facilities in military need to be changed, and in particular, ammunition depots for wartime occupy a large number of sites, so management policies need to be improved. The Ministry of National Defense is presenting the design of the underground ammunition depot according to the guidelines, but concrete improvements are needed in consideration of wartime preparation. Our study aims to explore the importance and priorities of how to utilize the technology of the 4th Industrial Revolution necessary for smartization of underground ammunition depots for implementing Defense Innovation 4.0. To this end, the present study conducted an AHP analysis based on the criteria (guard, safety, environment, logistics system, equipment facilities, and life management) to be considered as a smartization plan for underground ammunition depots, and the need to apply it in the relative importance of AI, IoT, big data, cloud, and robots was confirmed. As a result of the analysis, this paper has shown that it is necessary to strengthen the safety and guard-related systems of underground ammunition depots in the future, and to monitor the condition of ammunition using IoT and AI and pursue efficient operation. This study provides practical and academical considerations for future research. priority determination and policy implementation using the 4th Industrial Revolution technology are required for the effective construction and operation of smart underground ammunition depots. Subsequent studies need to expand the underground ammunition depot in consideration of the characteristics of the weapon system, taking into account the safety and availability considering the total cycle.

The 2011 US Billion‐Ton Update estimates that by 2030 there will be enough agricultural and forest resources to sustainably provide at least one billion dry tons of biomass annually, enough to displace approximately 30% of the country's current petroleum consumption. A portion of these resources are inaccessible at current cost targets with conventional feedstock supply systems because of their remoteness or low yields. Reliable analyses and projections of US biofuels production depend on assumptions about the supply system and biorefinery capacity, which, in turn, depend upon economic value, feedstock logistics, and sustainability. A cross‐functional team has examined combinations of advances in feedstock supply systems and biorefinery capacities with rigorous design information, improved crop yield and agronomic practices, and improved estimates of sustainable biomass availability. A previous report on biochemical refinery capacity noted that under advanced feedstock logistic supply systems that include depots and pre‐processing operations there are cost advantages that support larger biorefineries up to 10 000 DMT/day facilities compared to the smaller 2000 DMT/day facilities. This report focuses on analyzing conventional versus advanced depot biomass supply systems for a thermochemical conversion and refinery sizing based on woody biomass. The results of this analysis demonstrate that the economies of scale enabled by advanced logistics offsets much of the added logistics costs from additional depot processing and transportation, resulting in a small overall increase to the minimum ethanol selling price compared to the conventional logistic supply system. While the overall costs do increase slightly for the advanced logistic supply systems, the ability to mitigate moisture and ash in the system will improve the storage and conversion processes. In addition, being able to draw on feedstocks from further distances will decrease the risk of biomass supply to the conversion facility.

The purpose of making efficient and flexible manufacturing systems is often related to the possibility to analyze the system considering at the same time a wide number of parameters and their interactions. Simulation models are proved to be useful to support and drive company management in improving the performances of production and logistic systems. However, to achieve the expected results, a detailed model of the production and logistic system is needed as well as a structured error analysis to guarantee results reliability. The aim of this paper is to give some practical guide lines in order to drive the error analysis for discrete event stochastic simulation model that are widely used to study production and logistic system.Keywordsdiscrete eventsimulation modelerror analysisstochastic model