Pub Date : 2023-04-26DOI: 10.1177/00375497231168630
Salma Lahmar, M. Maalmi, R. Idchabani
Multiobjective building design optimization is a challenging problem because it involves finding a set of solutions that simultaneously optimize multiple conflicting objectives. Simulations-based optimization is widely used, but it is a computationally expensive process in terms of time, as it requires a large number of evaluations of the objective functions. Metamodel-based optimization is an alternative to reduce the time-consuming simulations during the optimization process. Metamodels can approximate the building simulation model with analytical expressions. However, the accuracy of metamodels depends on the number of simulations used to train the model and the sampling strategy used to select informative samples over the design space. This study proposes an efficient sequential sampling approach to fit the metamodels toward the regions of the design space where their accuracy is higher and can improve all objectives simultaneously. To demonstrate the effectiveness of this approach, it was applied to optimize the energy and investment costs of a multi-story residential building. The optimization results were compared with those obtained using a non-dominated sorted genetic algorithm II (NSGA-II). The results of this study show that the proposed method reduces the number of building energy simulations required by up to 50% while guaranteeing accurate optimization results. Fifteen energy-efficient buildings designs were proposed, with a wide range of trade-offs between energy and investment costs. This study highlights the potential of the proposed approach to achieve faster and accurate building design optimization and allowing for a larger design space, leading to more creative and innovative solutions.
{"title":"Multiobjective building design optimization using an efficient adaptive Kriging metamodel","authors":"Salma Lahmar, M. Maalmi, R. Idchabani","doi":"10.1177/00375497231168630","DOIUrl":"https://doi.org/10.1177/00375497231168630","url":null,"abstract":"Multiobjective building design optimization is a challenging problem because it involves finding a set of solutions that simultaneously optimize multiple conflicting objectives. Simulations-based optimization is widely used, but it is a computationally expensive process in terms of time, as it requires a large number of evaluations of the objective functions. Metamodel-based optimization is an alternative to reduce the time-consuming simulations during the optimization process. Metamodels can approximate the building simulation model with analytical expressions. However, the accuracy of metamodels depends on the number of simulations used to train the model and the sampling strategy used to select informative samples over the design space. This study proposes an efficient sequential sampling approach to fit the metamodels toward the regions of the design space where their accuracy is higher and can improve all objectives simultaneously. To demonstrate the effectiveness of this approach, it was applied to optimize the energy and investment costs of a multi-story residential building. The optimization results were compared with those obtained using a non-dominated sorted genetic algorithm II (NSGA-II). The results of this study show that the proposed method reduces the number of building energy simulations required by up to 50% while guaranteeing accurate optimization results. Fifteen energy-efficient buildings designs were proposed, with a wide range of trade-offs between energy and investment costs. This study highlights the potential of the proposed approach to achieve faster and accurate building design optimization and allowing for a larger design space, leading to more creative and innovative solutions.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":"1 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84449152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-05DOI: 10.1177/00375497231161146
Xiao-Ting Yuan, Tie-Qiao Tang, Liang Chen, Tao Wang
A cellular automaton (CA) model with a finer discretization of space is proposed to simulate a non-emergency evacuation process in a room with an obstacle. During the evacuation process, a triangle “evading region” phenomenon has been observed through simulation and experiment on the upstream side of the spatial obstacle. In this paper, we use a simple method to generate an obstacle floor field corresponding to the triangle. We investigate the relationship between the pedestrian trajectories and the obstacle’s position. We also study the effect of the obstacle on evacuation time and average evacuation speed. Our study provides insights into the simulation of obstacle avoidance behavior of pedestrians in simple scenarios.
{"title":"A fine grid cellular automaton model for pedestrian evacuation considering the effect of an obstacle","authors":"Xiao-Ting Yuan, Tie-Qiao Tang, Liang Chen, Tao Wang","doi":"10.1177/00375497231161146","DOIUrl":"https://doi.org/10.1177/00375497231161146","url":null,"abstract":"A cellular automaton (CA) model with a finer discretization of space is proposed to simulate a non-emergency evacuation process in a room with an obstacle. During the evacuation process, a triangle “evading region” phenomenon has been observed through simulation and experiment on the upstream side of the spatial obstacle. In this paper, we use a simple method to generate an obstacle floor field corresponding to the triangle. We investigate the relationship between the pedestrian trajectories and the obstacle’s position. We also study the effect of the obstacle on evacuation time and average evacuation speed. Our study provides insights into the simulation of obstacle avoidance behavior of pedestrians in simple scenarios.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":"4 1","pages":"957 - 968"},"PeriodicalIF":1.6,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72475141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-31DOI: 10.1177/00375497231164645
S. Djeffal, Chawki Mahfoudi
Multi-section continuum robots’ (CRs) behavior is still an outstanding problem because of the highly non-linearity of its equation of motions. To this end, in this paper, particle swarm optimization (PSO) is adopted to solve the inverse kinematic model (IKM) of CRs. First, the CR’s structure is properly described. Then, the aforementioned algorithm is elaborately discussed and implemented in figuring out the IKM of CR and verified through forward kinematic model by choosing the PSO parameters, namely, cognitive factors ( C 1 = C 2 = 1 . 2 ) and inertia weight ( ω = 0 . 79 ) for 200 positions on an arc-like trajectory. The optimal angle values ( θ = 0 . 0346 and φ = 0 . 00013 ) which ensure the lowest distance between the attainably desired position and the robot’s end effector are 1 . 04497 × 10 − 9 mm which is perfectly accurate. After that, simulation through MATLAB is carried out, namely, in the first simulation, a three-section CR follows a linear trajectory with a precision approximately equal to 0 . 75 × 10 − 9 mm . Furthermore, PSO takes 7 ms as a mean consumption time to make the robot’s end effector attain to each position. Then, a circular trajectory is followed using PSO. Comparatively speaking, PSO is compared with four meta-heuristic approaches; it is remarked that PSO is a good compromise between accuracy and time consumption. Based on the obtained results, PSO can be considered as a trade-off between accuracy and time consumption for solving the IKM of CRs with complex structure.
{"title":"Inverse kinematic model of multi-section continuum robots using particle swarm optimization and comparison to four meta-heuristic approaches","authors":"S. Djeffal, Chawki Mahfoudi","doi":"10.1177/00375497231164645","DOIUrl":"https://doi.org/10.1177/00375497231164645","url":null,"abstract":"Multi-section continuum robots’ (CRs) behavior is still an outstanding problem because of the highly non-linearity of its equation of motions. To this end, in this paper, particle swarm optimization (PSO) is adopted to solve the inverse kinematic model (IKM) of CRs. First, the CR’s structure is properly described. Then, the aforementioned algorithm is elaborately discussed and implemented in figuring out the IKM of CR and verified through forward kinematic model by choosing the PSO parameters, namely, cognitive factors ( C 1 = C 2 = 1 . 2 ) and inertia weight ( ω = 0 . 79 ) for 200 positions on an arc-like trajectory. The optimal angle values ( θ = 0 . 0346 and φ = 0 . 00013 ) which ensure the lowest distance between the attainably desired position and the robot’s end effector are 1 . 04497 × 10 − 9 mm which is perfectly accurate. After that, simulation through MATLAB is carried out, namely, in the first simulation, a three-section CR follows a linear trajectory with a precision approximately equal to 0 . 75 × 10 − 9 mm . Furthermore, PSO takes 7 ms as a mean consumption time to make the robot’s end effector attain to each position. Then, a circular trajectory is followed using PSO. Comparatively speaking, PSO is compared with four meta-heuristic approaches; it is remarked that PSO is a good compromise between accuracy and time consumption. Based on the obtained results, PSO can be considered as a trade-off between accuracy and time consumption for solving the IKM of CRs with complex structure.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":"23 1","pages":"817 - 830"},"PeriodicalIF":1.6,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81541507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-29DOI: 10.1177/00375497231163642
Songhua Huang, Yugong Xu, Zhaoxin Liu, W. Dou, Lele Zhang
Simulating three-dimensional acoustic problems with traditional finite element models (FEMs) may result in a large dispersion error that is difficult to manage. To control dispersion error caused by “overly stiff” features of FEM, a face-based smoothed FEM (FS-FEM) model was used to analyze the sound field of a high-speed train. Based on the acoustic Galerkin method’s weak form, smooth regions were reconstructed within the original finite element area, and numerical simulations were performed in MATLAB. Modal analysis of a test example revealed that results obtained using FS-FEM are more accurate than those obtained using the traditional FEM. Finally, it was used to calculate the sound field of China Railway High-speed 380B (CRH380B) high-speed trains in time and frequency domains, achieving higher accuracy than the traditional approach. Results were more akin to the realistic solution, which demonstrated the performance of the FS-FEM.
{"title":"Face-based smoothed finite element method for simulating the sound field of a high-speed train","authors":"Songhua Huang, Yugong Xu, Zhaoxin Liu, W. Dou, Lele Zhang","doi":"10.1177/00375497231163642","DOIUrl":"https://doi.org/10.1177/00375497231163642","url":null,"abstract":"Simulating three-dimensional acoustic problems with traditional finite element models (FEMs) may result in a large dispersion error that is difficult to manage. To control dispersion error caused by “overly stiff” features of FEM, a face-based smoothed FEM (FS-FEM) model was used to analyze the sound field of a high-speed train. Based on the acoustic Galerkin method’s weak form, smooth regions were reconstructed within the original finite element area, and numerical simulations were performed in MATLAB. Modal analysis of a test example revealed that results obtained using FS-FEM are more accurate than those obtained using the traditional FEM. Finally, it was used to calculate the sound field of China Railway High-speed 380B (CRH380B) high-speed trains in time and frequency domains, achieving higher accuracy than the traditional approach. Results were more akin to the realistic solution, which demonstrated the performance of the FS-FEM.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":"27 1","pages":"1057 - 1067"},"PeriodicalIF":1.6,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75645526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-29DOI: 10.1177/00375497231165049
Haben Yhdego, Nahom Kidane, F. McKenzie, M. Audette
Cardiac auscultation (CA), the act of listening to the heart’s sound, is a critical skill that provides valuable information for identifying serious heart diseases. Proficiency in cardiac auscultation requires repeated stethoscope practice and experience in identifying abnormal or irregular cardiac rhythms. However, nowadays, most hospital admissions are short and intensely focused, with fewer opportunities for medical trainees to learn and practice bedside examination skills. It is common practice in many institutions to incorporate standardized patients (SPs) into CA training because these actors are able to represent the patient and convey the symptoms. However, SPs are typically healthy individuals, limiting the kinds of abnormalities that students can hear. In this work, we develop a novel real-time simulation-based method for virtual pathology stethoscope (VPS) detection. The VPS system uses augmented reality (AR) to teach medical students how to perform cardiac examinations by listening to abnormal heart sounds in SPs who are otherwise healthy. A digital stethoscope with two electrodes on the chest piece collects electrocardiogram (ECG) signal data sets from SPs at the four primary auscultation sites. Next, different deep-learning methods are evaluated for classifying the location of the stethoscope by taking advantage of subtle differences in the ECG signals. This study would significantly extend the simulation capabilities of SPs by allowing medical students and trainees to perform realistic CA and hear CA in a clinical environment.
{"title":"Development of deep-learning models for a hybrid simulation of auscultation training on standard patients using an ECG-based virtual pathology stethoscope","authors":"Haben Yhdego, Nahom Kidane, F. McKenzie, M. Audette","doi":"10.1177/00375497231165049","DOIUrl":"https://doi.org/10.1177/00375497231165049","url":null,"abstract":"Cardiac auscultation (CA), the act of listening to the heart’s sound, is a critical skill that provides valuable information for identifying serious heart diseases. Proficiency in cardiac auscultation requires repeated stethoscope practice and experience in identifying abnormal or irregular cardiac rhythms. However, nowadays, most hospital admissions are short and intensely focused, with fewer opportunities for medical trainees to learn and practice bedside examination skills. It is common practice in many institutions to incorporate standardized patients (SPs) into CA training because these actors are able to represent the patient and convey the symptoms. However, SPs are typically healthy individuals, limiting the kinds of abnormalities that students can hear. In this work, we develop a novel real-time simulation-based method for virtual pathology stethoscope (VPS) detection. The VPS system uses augmented reality (AR) to teach medical students how to perform cardiac examinations by listening to abnormal heart sounds in SPs who are otherwise healthy. A digital stethoscope with two electrodes on the chest piece collects electrocardiogram (ECG) signal data sets from SPs at the four primary auscultation sites. Next, different deep-learning methods are evaluated for classifying the location of the stethoscope by taking advantage of subtle differences in the ECG signals. This study would significantly extend the simulation capabilities of SPs by allowing medical students and trainees to perform realistic CA and hear CA in a clinical environment.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":"29 1","pages":"903 - 915"},"PeriodicalIF":1.6,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80012905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-24DOI: 10.1177/00375497231157384
Audun Stolpe, I. Rummelhoff, J. Hannay
Simulation games are designed to cultivate expertise and rehearse particular skill sets. To yield longitudinal effects, sequences of events must be crafted to yield intended learning outcomes, sometimes by focusing on particularly difficult situations and replaying variants. The present paper develops a logic-based approach for encoding the interrelation between action, events, and objects in a manner that allows the resulting scenario description to immediately be executed in a game development environment. This has the dual effect of decoupling the description of a scenario from the simulation platform itself, as well as supporting iterative and flexible development of learning content. To this end, we provide three interrelated components: First, we develop a scenario description language based on Answer Set Programming. The language is designed to allow an automated reasoner to deduce a schedule of the future events that are caused by an action taken in a given simulation environment. Second, we define a protocol for exchanging actions and computed futures between, respectively, the simulation environment and the external automated reasoner. Finally, as a proof of concept, we develop an Application Programming Interface (API) for the Unity Real-Time Development Platform that implements the protocol and offers a software framework for connecting the computed future events to concrete game objects. This allows the game to evolve coherently from the specification. We argue that the resulting system inherits capabilities for artificial commonsense reasoning from its declarative basis which are useful for reasoning about an evolving emergency incident or training scenario.
{"title":"A logic-based event controller for means-end reasoning in simulation environments","authors":"Audun Stolpe, I. Rummelhoff, J. Hannay","doi":"10.1177/00375497231157384","DOIUrl":"https://doi.org/10.1177/00375497231157384","url":null,"abstract":"Simulation games are designed to cultivate expertise and rehearse particular skill sets. To yield longitudinal effects, sequences of events must be crafted to yield intended learning outcomes, sometimes by focusing on particularly difficult situations and replaying variants. The present paper develops a logic-based approach for encoding the interrelation between action, events, and objects in a manner that allows the resulting scenario description to immediately be executed in a game development environment. This has the dual effect of decoupling the description of a scenario from the simulation platform itself, as well as supporting iterative and flexible development of learning content. To this end, we provide three interrelated components: First, we develop a scenario description language based on Answer Set Programming. The language is designed to allow an automated reasoner to deduce a schedule of the future events that are caused by an action taken in a given simulation environment. Second, we define a protocol for exchanging actions and computed futures between, respectively, the simulation environment and the external automated reasoner. Finally, as a proof of concept, we develop an Application Programming Interface (API) for the Unity Real-Time Development Platform that implements the protocol and offers a software framework for connecting the computed future events to concrete game objects. This allows the game to evolve coherently from the specification. We argue that the resulting system inherits capabilities for artificial commonsense reasoning from its declarative basis which are useful for reasoning about an evolving emergency incident or training scenario.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":"54 1","pages":"831 - 858"},"PeriodicalIF":1.6,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86394894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-21DOI: 10.1177/00375497231158930
Philipp Andelfinger, A. Uhrmacher
Traditionally, parallel discrete-event simulations of agent-based models in continuous time are organized around logical processes exchanging time-stamped events, which clashes with the properties of models in which tightly coupled agents frequently and instantaneously access each other’s states. To illustrate the challenges of such models and to derive a solution, we consider the domain-specific modeling language ML3, which allows modelers to succinctly express transitions and interactions of linked agents based on a continuous-time Markov chain (CTMC) semantics. We propose synchronous optimistic synchronization algorithms tailored toward simulations of fine-grained interactions among tightly coupled agents in highly dynamic topologies and present implementations targeting multicore central processing units (CPUs) as well as many-core graphics processing units (GPUs). By dynamically restricting the temporal progress per round to ensure that at most one transition or state access per agent, the synchronization algorithms enable efficient direct agent interaction and limit the required agent state history to only a single current and projected state. To maintain concurrency given actions that depend on dynamically updated macro-level properties, we introduce a simple relaxation scheme with guaranteed error bounds. Using an extended variant of the classical susceptible-infected-recovered network model, we benchmark and profile the performance of the different algorithms running on CPUs and on a data center GPU.
{"title":"Synchronous speculative simulation of tightly coupled agents in continuous time on CPUs and GPUs","authors":"Philipp Andelfinger, A. Uhrmacher","doi":"10.1177/00375497231158930","DOIUrl":"https://doi.org/10.1177/00375497231158930","url":null,"abstract":"Traditionally, parallel discrete-event simulations of agent-based models in continuous time are organized around logical processes exchanging time-stamped events, which clashes with the properties of models in which tightly coupled agents frequently and instantaneously access each other’s states. To illustrate the challenges of such models and to derive a solution, we consider the domain-specific modeling language ML3, which allows modelers to succinctly express transitions and interactions of linked agents based on a continuous-time Markov chain (CTMC) semantics. We propose synchronous optimistic synchronization algorithms tailored toward simulations of fine-grained interactions among tightly coupled agents in highly dynamic topologies and present implementations targeting multicore central processing units (CPUs) as well as many-core graphics processing units (GPUs). By dynamically restricting the temporal progress per round to ensure that at most one transition or state access per agent, the synchronization algorithms enable efficient direct agent interaction and limit the required agent state history to only a single current and projected state. To maintain concurrency given actions that depend on dynamically updated macro-level properties, we introduce a simple relaxation scheme with guaranteed error bounds. Using an extended variant of the classical susceptible-infected-recovered network model, we benchmark and profile the performance of the different algorithms running on CPUs and on a data center GPU.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":"43 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91335711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-17DOI: 10.1177/00375497231159944
Wen Jun Tan, Philipp Andelfinger, Wentong Cai, D. Eckhoff, Alois Knoll
Applying simulation-based optimization to city-scale traffic signal optimization can be challenging due to the large search space resulting in high computational complexity. A divide-and-conquer approach can be used to partition the problem and optimized separately, which leads to faster convergence. However, the lack of coordination among the partial solutions may yield a poor-quality global solution. In this paper, we propose a new method for simulation-based optimization of traffic signal control, called spatially iterative coordination for parallel optimization (SICPO), to improve coordination among the partial solutions and reduce synchronization between the partitioned regions. The traffic scenario is simulated to obtain the interactions, which is used to spatially decompose the scenario into regions and identify interdependencies between the regions. Based on the regions, the problem is divided into subproblems which are optimized separately. To coordinate between the subproblems, the interactions between partial solutions are synchronized in two ways. First, multiple iterations of the optimization process can be executed to coordinate the partial solutions at the end of each optimization process. Second, the partial solutions can also be coordinated among the regions by synchronizing the trips across the regions. To reduce computational complexity, parallelism can be applied on two levels: each region is optimized concurrently, and each solution for a region is evaluated in parallel. We demonstrate our method on a real-world road network of Singapore, where SICPO converges to an average travel time 21.6% faster than global optimization at 62.8× shorter wall-clock time.
{"title":"Spatial iterative coordination for parallel simulation-based optimization of large-scale traffic signal control","authors":"Wen Jun Tan, Philipp Andelfinger, Wentong Cai, D. Eckhoff, Alois Knoll","doi":"10.1177/00375497231159944","DOIUrl":"https://doi.org/10.1177/00375497231159944","url":null,"abstract":"Applying simulation-based optimization to city-scale traffic signal optimization can be challenging due to the large search space resulting in high computational complexity. A divide-and-conquer approach can be used to partition the problem and optimized separately, which leads to faster convergence. However, the lack of coordination among the partial solutions may yield a poor-quality global solution. In this paper, we propose a new method for simulation-based optimization of traffic signal control, called spatially iterative coordination for parallel optimization (SICPO), to improve coordination among the partial solutions and reduce synchronization between the partitioned regions. The traffic scenario is simulated to obtain the interactions, which is used to spatially decompose the scenario into regions and identify interdependencies between the regions. Based on the regions, the problem is divided into subproblems which are optimized separately. To coordinate between the subproblems, the interactions between partial solutions are synchronized in two ways. First, multiple iterations of the optimization process can be executed to coordinate the partial solutions at the end of each optimization process. Second, the partial solutions can also be coordinated among the regions by synchronizing the trips across the regions. To reduce computational complexity, parallelism can be applied on two levels: each region is optimized concurrently, and each solution for a region is evaluated in parallel. We demonstrate our method on a real-world road network of Singapore, where SICPO converges to an average travel time 21.6% faster than global optimization at 62.8× shorter wall-clock time.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":"1 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82085447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-14DOI: 10.1177/00375497221151188
Wayne Pearson, Mohammed Islam, M. Lau, R. Gash, Jason Mills
This paper describes a high-fidelity numerical model that simulates vessel stationkeeping operations in ice-rich waters. The discrete event simulation engine incorporates several novel features, including new ice floe failure models for bow and midships locations; an ice floe creation strategy that facilitates rafting of ice floes; and a vessel thruster model that takes into account physical limitations such as thruster angle slew rates and propeller ramp rates. It accommodates a wide range of ice field specifications and runs in real-time on a standard desktop personal computer (Intel® Core™ i7 Processor or equivalent). The model has been validated using physical measurements of a generic drillship model in several broken ice conditions; it predicted thruster forces and motions that were comparable to those observed during dynamic positioning operations.
{"title":"Discrete event simulation of vessel stationkeeping operations in ice-rich waters","authors":"Wayne Pearson, Mohammed Islam, M. Lau, R. Gash, Jason Mills","doi":"10.1177/00375497221151188","DOIUrl":"https://doi.org/10.1177/00375497221151188","url":null,"abstract":"This paper describes a high-fidelity numerical model that simulates vessel stationkeeping operations in ice-rich waters. The discrete event simulation engine incorporates several novel features, including new ice floe failure models for bow and midships locations; an ice floe creation strategy that facilitates rafting of ice floes; and a vessel thruster model that takes into account physical limitations such as thruster angle slew rates and propeller ramp rates. It accommodates a wide range of ice field specifications and runs in real-time on a standard desktop personal computer (Intel® Core™ i7 Processor or equivalent). The model has been validated using physical measurements of a generic drillship model in several broken ice conditions; it predicted thruster forces and motions that were comparable to those observed during dynamic positioning operations.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":"66 1","pages":"729 - 753"},"PeriodicalIF":1.6,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78681213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-24DOI: 10.1177/00375497231156618
Fabiano Bhering, Diego Passos, Katia Obraczka, Célio Albuquerque
Estimating the performance of multimedia (MM) traffic is important in numerous contexts, including routing and forwarding, quality of service (QoS) provisioning, and adaptive video streaming. This paper proposes a network performance estimator which aims at providing, in quasi real-time, network performance estimates for IoT MM traffic in IEEE 802.11 multihop wireless networks. To our knowledge, the proposed MM-aware performance estimator, or MAPE, is the first deterministic simulation-based estimator that provides real-time per-flow throughput, packet loss, and delay estimates while considering inter-flow interference and multirate flows, typical of MM traffic. Our experimental results indicate that MAPE is able to provide network performance estimates that can be used by IoT MM services, notably to inform real-time route selection in IoT video transmission, at a fraction of the execution time when compared to stochastic network simulators. When compared to existing deterministic simulators, MAPE yields higher accuracy at comparable execution times due to its ability to consider multirate flows.
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