{"title":"Integrating consumer preferences in renewable energy expansion planning using agent-based modeling","authors":"A. Mittal, Caroline C. Krejci","doi":"10.1109/WSC.2017.8247995","DOIUrl":"https://doi.org/10.1109/WSC.2017.8247995","url":null,"abstract":"As share of renewable sources in the energy sector is increasing, the energy production and distribution network's centralized structure is changing to numerous small-scale distributed networks. Energy consumers in the residential sector are increasingly becoming energy producers by adopting rooftop photo voltaic (PV) systems. However, increasing rooftop PV adoption has contributed to diminishing revenues for utility companies. This paper describes an agent-based model that has been developed to help utility companies better understand the impacts of consumers' preferences and behaviors on adding renewable sources to their energy mix. Experimental results demonstrate that including both consumers and utility companies as stakeholders can help the utilities alleviate revenue losses due to increasing rooftop PV adoption while meeting their renewable energy expansion targets.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125217648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thomas Sobottka, Felix Kamhuber, J. Henjes, W. Sihn
{"title":"A case study for simulation and optimization based planning of production and logistics systems","authors":"Thomas Sobottka, Felix Kamhuber, J. Henjes, W. Sihn","doi":"10.1109/WSC.2017.8248064","DOIUrl":"https://doi.org/10.1109/WSC.2017.8248064","url":null,"abstract":"This paper introduces a practical approach for the comprehensive simulation based planning and optimization of the production and logistics of a discrete goods manufacturer. Although simulation and optimization are well-established planning aides in production and logistics, their actual application in the field is still scarce, especially in small and medium-sized enterprises (SMEs). This is largely due to the complexity of the planning task and lack of practically applicable approaches for real-life planning scenarios. This paper provides a case study from the food industry, featuring a comprehensive planning approach based on simulation and optimization. The approach utilizes an offline-coupled multilevel simulation to smooth production and logistics planning via optimization, to optimally configure the production system using discrete-event simulation and to optimize the logistics network utilizing an agent-based simulation. The connected simulation and optimization modules can enhance the production logistics significantly, potentially providing a reference approach for similar industry applications.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125268454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A hybrid approach for building models and simulations for smart cities: Expert knowledge and low dimensionality","authors":"Elhabib Moustaid, S. Meijer","doi":"10.1109/WSC.2017.8247896","DOIUrl":"https://doi.org/10.1109/WSC.2017.8247896","url":null,"abstract":"In face of high urbanization and increasing mobility, models and simulations are used to find answers for urban planning problems. However, simulations face criticism for over-simplifying complex reality, having models disconnected from the context of their use or excluding policy-makers from the building of models. Smart city approaches did not overcome that reality even if they relied more and more on microscopic models, together with data available through technology. This article describes a hybrid approach combining the expert knowledge on the city and its limits in terms of data, with models having the right dimensionality to provide policy-makers and urban managers with the necessary information for understanding and managing the city. This approach has been applied in Venice, but it describes in more general terms a way of bridging the world of theoretically sound models with their potential use.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125403556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A hybrid simulation model of helping behavior","authors":"J. Green, Caroline C. Krejci, D. Cantor","doi":"10.1109/WSC.2017.8247902","DOIUrl":"https://doi.org/10.1109/WSC.2017.8247902","url":null,"abstract":"Companies in a variety of industries rely on their employees to work together effectively in teams to achieve their objectives. However, finding ways to encourage collaborative behavior to optimize a team's performance is often challenging. In particular, managers would like to be able to increase the likelihood that team members decide to help each other, in the event of workload imbalances. In this paper, a hybrid simulation (ABM-DES) model has been developed to investigate how workers' predisposition to altruistic tendencies, an important personality factor, influences their willingness to help their co-workers on a production task. Model inputs were derived from experimental data, including participants' personalities, perceptions, and decisions regarding whether or not to help team members complete a task. Simulation results suggest that highly altruistic individuals are more likely to help their co-workers.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129946515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Neural networks and agent-based diffusion models","authors":"A. Negahban","doi":"10.1109/WSC.2017.8247884","DOIUrl":"https://doi.org/10.1109/WSC.2017.8247884","url":null,"abstract":"This paper introduces a new consumer decision-making model where each agent uses a neural network to evaluate word-of-mouth and predict her utility prior to adoption a new product based on her experiences in the past. The model considers the fact that consumers may not know their true preferences before experiencing the product. By using a neural network, an agent can: (1) interpret the feedback from a neighbor who has conflicting preferences with her; (2) interpret partially positive and/or negative feedback; and, (3) assign different weights to the feedback received from different neighbors. The model is implemented in an agent-based simulation model to verify that the resulting diffusion dynamics follow a typical diffusion curve. Preliminary experiments with the model also provide interesting results about the effect of the number of product attributes on the quality of an individual's utility prediction as well as proportion of satisfied adopters.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130097574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Characterization of the underlying mechanisms of vulnerability in complex projects using dynamic network simulation","authors":"Jin Zhu, A. Mostafavi","doi":"10.1109/WSC.2017.8247973","DOIUrl":"https://doi.org/10.1109/WSC.2017.8247973","url":null,"abstract":"The objective of this study was to investigate the underlying mechanisms of vulnerability in complex construction projects using simulation experiments. Specifically, two hypotheses related to project vulnerability were tested: (1) project schedule performance is negatively correlated with vulnerability; (2) the level of project vulnerability is positively correlated with project exposure to uncertainty and organizational complexity. In the proposed dynamic network simulation methodology, construction projects are modeled as heterogeneous meta-networks. Project vulnerability is assessed by the decrease in meta-network efficiency due to uncertainty-induced perturbations. Project schedule deviation is used as a measure for quantifying the impacts of vulnerability on project performance outcomes. The proposed simulation methodology was implemented in three case studies of real-world construction projects. Monte-Carlo simulation experiments were conducted under different simulation scenarios consisting of varying levels of uncertainty and project planning strategies to test the hypotheses.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129530598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Simulation-based predictive analytics for dynamic queueing systems","authors":"Huiyin Ouyang, B. Nelson","doi":"10.1109/WSC.2017.8247910","DOIUrl":"https://doi.org/10.1109/WSC.2017.8247910","url":null,"abstract":"Simulation and simulation optimization have primarily been used for static system design problems based on long-run average performance measures. Control or policy-based optimization has been a weakness, because it requires a way to predict future behavior based on current state and time information. This work is a first step in that direction with a focus on congestion measures for queueing systems. The idea is to fit predictive models to dynamic sample paths of the system state from a detailed simulation. We propose a two-step method to dynamically predict the probability that the system state belongs to a certain subset and test the performance of this method on two examples.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129673382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Haobin Li, Xiuju FU, Xiaofeng Yin, Giulia Pedrielli, L. Lee
{"title":"Optimal design of master-worker architecture for parallelized simulation optimization","authors":"Haobin Li, Xiuju FU, Xiaofeng Yin, Giulia Pedrielli, L. Lee","doi":"10.1109/WSC.2017.8247950","DOIUrl":"https://doi.org/10.1109/WSC.2017.8247950","url":null,"abstract":"This study formulates and solves the design problem for a master-worker architecture dedicated to the implementation of a parallelized simulation optimization algorithm. Such a formulation does not assume any specific characteristic of the optimization problem being solved, but the way the algorithm is parallelized. In particular, we refer to the master-worker paradigm, where the master makes sampling decisions while the workers receive solutions to evaluate. We identify two metrics to be optimized: the throughput of the workers in terms of the number of evaluations per time unit, and the lack of synchronization between the master and the workers. We identify several design parameters: number of workers (n), the buffer size for each worker and for the master and the sample size m, i.e., the number of solutions used by the master for sampling decisions at each iteration. Numerical experiments show optimal designs over randomly generated simulation optimization algorithm instances.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129543707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammed Mesabbah, S. Rahoui, Mohamed A. F. Ragab, A. Mahfouz, A. Arisha
{"title":"Seasonal recruiting policies for table grape packing operations: A hybrid simulation modelling study","authors":"Mohammed Mesabbah, S. Rahoui, Mohamed A. F. Ragab, A. Mahfouz, A. Arisha","doi":"10.1109/WSC.2017.8247907","DOIUrl":"https://doi.org/10.1109/WSC.2017.8247907","url":null,"abstract":"The packing process is a critical post-harvesting activity in table grape industry. Workers in packing stations are hired under seasonal contracts because of product seasonality and operations labor intensity. Seasonal workers, however, are usually characterized by inconsistent performance, high turnover and experience variation which leads to low productivity and high waste. Few mathematical models were used for evaluating fresh products packing operations, but in a deterministic nature which hinders the complexity and dynamics of the business processes. Hence, a hybrid Discrete Event Simulation (DES) and Agent-Based Modelling (ABM) are employed to evaluate a set of seasonal recruiting policies in a large grape packing station. The paper aims to investigate the impact of workers experience on packing operations efficiency. The model outcomes demonstrate the improvement in operations efficiency and total running cost (about 20% savings) that can be achieved when applying optimal recruiting policies that reduce labors variations.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124620550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Building an integrated simulation environment for modeling traffic management interactions","authors":"S. Tien, David J. Bodoh, Huina Gao, J. DeArmon","doi":"10.1109/WSC.2017.8247988","DOIUrl":"https://doi.org/10.1109/WSC.2017.8247988","url":null,"abstract":"The Federal Aviation Administration (FAA) is funding and encouraging new concepts for improving air traffic flow management (TFM) decision-making. The resulting automation capabilities will need to be operationally integrated into the existing air traffic management (ATM) system. Understanding how a new capability will interact with existing system components is challenging because of the range of possible real-world situations, which must be handled by the ATM system. Although there are fast-time traffic simulation tools available for modeling the impact of TFM actions, they are often developed as stand-alone tools, which are not extensible or flexible to work in concert with other advanced TFM capabilities for conducting integration studies or quantifying benefits. To address this gap, we have built a fast-time, distributed simulation platform integrating state-of-the-art traffic simulator and allows the plug-in of advanced TFM prototypes — or other experimental capabilities that already exist — so their interactions can be studied. In this paper, we discuss the requirements and the necessary components for building this platform, which requires an architecture that is flexible enough to support many different configurations of modeling tools and applications. We then use a TFM integration case study to demonstrate the utility of the platform. We show, with only minor effort, a proposed TFM prototype can be plugged into the platform and its benefits can be evaluated.","PeriodicalId":145780,"journal":{"name":"2017 Winter Simulation Conference (WSC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128703749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}