scholarly journals Sustainable Humanitarian Operations: Multi-Method Simulation for Large-Scale Evacuation

2021 ◽  
Vol 13 (13) ◽  
pp. 7488
Author(s):  
Bertha Maya Sopha ◽  
Athaya Islami Triasari ◽  
Lynette Cheah

Integrating sustainability in humanitarian operations has been seen as a promising approach toward effective and long-term solutions. During disaster emergency management, the evacuation determines the risk of loss in a disaster. To better understand the effectiveness of the evacuation plan while considering the sustainability standpoint, this paper develops a multi-method simulation (MMS) approach to evaluate evacuation time, load balance of the shelters, and CO2 emission. The MMS integrating Agent-Based Modeling (ABM) and Discrete-Event Simulation (DES) incorporates evacuation decision-making and evacuation processes. Comparative analysis shows that the MMS outperforms the use of ABM solely. The simulation results indicate over-utilization and imbalanced load among the shelters, implying a need to expand shelters’ capacity and to revisit the evacuation plan concerning the location of the assembly points and the shelters and the resource allocation. Evacuation behavior heading to the nearest assembly point instead of the designated assembly point based on the evacuation plan worsens the imbalanced load among the shelters and results in higher CO2 emissions by 8%. The results demonstrate the necessity to include evacuation decision-making (social dimension) on top of the technical dimension and to adopt sustainable performance indicators in planning the evacuation sustainably. Avenues for future research are also discussed.

2021 ◽  
Vol 11 (21) ◽  
pp. 10397
Author(s):  
Barry Ezell ◽  
Christopher J. Lynch ◽  
Patrick T. Hester

Computational models and simulations often involve representations of decision-making processes. Numerous methods exist for representing decision-making at varied resolution levels based on the objectives of the simulation and the desired level of fidelity for validation. Decision making relies on the type of decision and the criteria that is appropriate for making the decision; therefore, decision makers can reach unique decisions that meet their own needs given the same information. Accounting for personalized weighting scales can help to reflect a more realistic state for a modeled system. To this end, this article reviews and summarizes eight multi-criteria decision analysis (MCDA) techniques that serve as options for reaching unique decisions based on personally and individually ranked criteria. These techniques are organized into a taxonomy of ratio assignment and approximate techniques, and the strengths and limitations of each are explored. We compare these techniques potential uses across the Agent-Based Modeling (ABM), System Dynamics (SD), and Discrete Event Simulation (DES) modeling paradigms to inform current researchers, students, and practitioners on the state-of-the-art and to enable new researchers to utilize methods for modeling multi-criteria decisions.


2021 ◽  
Vol 16 (93) ◽  
pp. 93-108
Author(s):  
David E. Sorokin ◽  

The author of this article represents his own work DVCompute Simulator, which is a collection of general-purpose programming libraries for discrete event simulation. The aim of the research was to create a set of simulators in the Rust language, efficient in terms of speed of execution, based on a unified approach and destined for different simulation modes. The simulators implement such modes as ordinary sequential simulation, nested simulation and distributed simulation. The article describes that nested simulation is related to Theory of Games, while distributed simulation can be used for running large-scale simulation models on supercomputers. It is shown how these different simulation modes can be implemented based on the single approach that combines many paradigms: the event-oriented paradigm, the process-oriented one, blocks similar to the GPSS language and even partially agent-based modeling. The author's approach is based on using the functional programming techniques, where the simulation model is defined as a composition of computations. The results of testing two modules are provided, where the modules support both the optimistic and conservative methods of distributed simulation.


Author(s):  
András Varga ◽  
Ahmet Y. Şekercioğlu Şekercioğlu

This paper reports a new parallel and distributed simulation architecture for OMNeT++, an open-source discrete event simulation environment. The primary application area of OMNeT++ is the simulation of communication networks. Support for a conservative PDES protocol (the Null Message Algorithm) and the relatively novel Ideal Simulation Protocol has been implemented.Placeholder modules, a novel way of distributing the model over several logical processes (LPs) is presented. The OMNeT++ PDES implementation has a modular and extensible architecture, allowing new synchronization protocols and new communication mechanisms to be added easily, which makes it an attractive platform for PDES research, too. We intend touse this framework to harness the computational capacity of highperformance cluster computersfor modeling very large scale telecommunication networks to investigate protocol performance and rare event failure scenarios.


2021 ◽  
Author(s):  
Dilshad Hassan Sallo ◽  
Gabor Kecskemeti

Discrete Event Simulation (DES) frameworks gained significant popularity to support and evaluate cloud computing environments. They support decision-making for complex scenarios, saving time and effort. The majority of these frameworks lack parallel execution. In spite being a sequential framework, DISSECT-CF introduced significant performance improvements when simulating Infrastructure as a Service (IaaS) clouds. Even with these improvements over the state of the art sequential simulators, there are several scenarios (e.g., large scale Internet of Things or serverless computing systems) which DISSECT-CF would not simulate in a timely fashion. To remedy such scenarios this paper introduces parallel execution to its most abstract subsystem: the event system. The new event subsystem detects when multiple events occur at a specific time instance of the simulation and decides to execute them either on a parallel or a sequential fashion. This decision is mainly based on the number of independent events and the expected workload of a particular event. In our evaluation, we focused exclusively on time management scenarios. While we did so, we ensured the behaviour of the events should be equivalent to realistic, larger-scale simulation scenarios. This allowed us to understand the effects of parallelism on the whole framework, while we also shown the gains of the new system compared to the old sequential one. With regards to scaling, we observed it to be proportional to the number of cores in the utilised SMP host.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Carolina Reis Gualberto ◽  
Lásara Fabrícia Rodrigues ◽  
Karine Araújo Ferreira

Purpose The purpose of this paper is to develop an approach to evaluate the partial postponement strategy and compare it with postponement and make-to-stock (MTS) strategies in the production of table wine in wineries in the state of Minas Gerais (south-eastern Brazil). Design/methodology/approach An approach based on discrete event simulation was developed to support decision-making in the wine sector. Simulation models were used to analyse partial postponement, postponement and MTS strategies in wine production. These models were inspired by a typical table wine producer selected from an exploratory study conducted in 12 wineries of Minas Gerais state in Brazil. Findings Hybrid strategies, such as partial postponement, favour the advantages of postponement and MTS depending on the portion of semi-finished and finished goods adopted. Wine production characteristics favour postponement and partial postponement with high semi-finished product levels (customer order-driven product) because this allows companies to reduce their inventory of bottles, despite possible increases in lost sales and costs. MTS and partial postponement with high finished product levels (forecast-driven product) present higher costs with bottled wine storage; however, these strategies reduce lost sales and improve agility and reliability in deliveries. Research limitations/implications Future research should analyse the production of table wines in other regions of the country and the production of fine wines. Practical implications The findings suggest promising perspectives for real-life applications in wineries in Brazil and other countries. Originality/value Simulation techniques allow the analysis of production strategies in little-known industries, such as table wine production in Brazil. The approach developed is flexible enough to support decisions and to be adapted to companies’ and markets’ characteristics and to test specific strategies.


Sign in / Sign up

Export Citation Format

Share Document