AN AGENT-BASED APPROACH FOR MODELING THE EFFECT OF LEARNING CURVE ON LABOR PRODUCTIVITY BRIDGES

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
H. Shehwaro ◽  
E. Zankoul ◽  
H. Khoury
Keyword(s):  
Learning Curve ◽  
Labor Productivity ◽  
Construction Projects ◽  
Discrete Event ◽  
Cost Savings ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Event Simulation ◽  
Adaptive Environment ◽  
Labor Resources

The labor-intensive nature of construction projects requires proper management and efficient utilization of labor resources. Improvement of labor productivity can enhance project performance and thereby lead to substantial time and cost savings. Several studies focused on identifying the effect of different factors on labor productivity, whereby the learning curve factor proved of paramount importance. Although previous research efforts developed models to represent the learning curve effect using traditional simulation approaches such as System Dynamics (SD) and Discrete Event Simulation (DES), none of these studies used Agent-Based Modeling (ABM) techniques. This study takes the initial steps and presents work targeted at analyzing the effect of learning on labor productivity using ABM. Based on ABM, a construction site can be modeled as an active environment in which agents interact with each other and their surroundings thereby creating an adaptive environment open for learning and improvement. The solution to the problem is described in details using a simulation model developed in AnyLogic 7 (Educational Version). The components of the proposed model have been created and preliminary results highlighted the potential of using the agent-based modeling paradigm to simulate the effect of learning on labor productivity in the construction industry

Multi-Methodology Approach

2021 ◽  
pp. 98-128
Keyword(s):  
System Dynamics ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Multiple Methods ◽  
Soft Systems ◽  
Agent Based ◽  
Event Simulation ◽  
Pluralistic Approach ◽  
The Difference

The pluralistic approach in today's world needs combining multiple methods, whether hard or soft, into a multi-methodology intervention. The methodologies can be combined, sometimes from several different paradigms, including hard and soft, in the form of a multi-methodology so that the hard paradigms are positivistic and see the organizational environment as objective, while the nature of soft paradigms is interpretive. In this chapter, the combination of methodologies has been examined using soft systems methodologies (SSM) and simulation methodologies including discrete event simulation (DES), system dynamics (SD), and agent-based modeling (ABM). Also, using the ontological, epistemological, and methodological assumptions underlying the respective paradigms, the difference between SD, ABM, SSM; a synthesis of SSM and SD generally known as soft system dynamics methodology (SSDM); and a promising integration of SSM and ABM referred to as soft systems agent-based methodology (SSABM) have been proven.

scholarly journals Digital plant: methods of discrete-event modeling and optimization of production characteristics

2021 ◽  
Vol 15 (2) ◽  
pp. 7-20
Author(s):  
Valery Makarov ◽  
Albert Bakhtizin ◽  
Gayane Beklaryan ◽  
Andranik Akopov
Keyword(s):  
Simulation Model ◽  
Hybrid Methods ◽  
Discrete Event ◽  
Agent Based ◽  
Event Simulation ◽  
Event Modeling ◽  
Technical Control ◽  
Assembly Unit ◽  
Labor Resources ◽  
Production Characteristics

This article presents a new approach to the development of a ‘digital twin’ of a manufacturing enterprise, using a television manufacturing plant as the case study. The feature of the proposed approach is the use of hybrid methods of agent-based modeling and discrete-event simulation in order to implement a simulation model of a complex production process for assembling final products from supplied components. The most important requirement for such a system is the integration of all key chains of a digital plant: conveyor lines, warehouses with components and final products (TVs), sorting and conveyor system, assembly unit, technical control department, packing unit, etc. The proposed simulation model is implemented in the AnyLogic system, which supports the possibility of using agent-based and discrete-event modeling methods within one model. The system also supports using the built-in genetic algorithm to optimize the main parameters of the model: the most important production characteristics (for example, assembly time of a product, the number of employees involved in assembly, quality control and packaging processes). Optimization experiments were completed with the help of the developed model at various intensities of loading conveyor lines with components, various restrictions on labor resources, etc. Three scenarios of the production system behavior are investigated: the absence of the components deficit with the possibility of significantly increasing the labor resource involved, a components deficit while demand for final products is maintained, and the presence of hard restrictions on the number of employees who can be involved in the processes under conditions of components deficit.

scholarly journals Methods for Weighting Decisions to Assist Modelers and Decision Analysists: A Review of Ratio Assignment and Approximate Techniques

2021 ◽  
Vol 11 (21) ◽  
pp. 10397
Author(s):  
Barry Ezell ◽  
Christopher J. Lynch ◽  
Patrick T. Hester
Keyword(s):  
Decision Making ◽  
Discrete Event Simulation ◽  
Computational Models ◽  
State Of The Art ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Decision Makers ◽  
Agent Based ◽  
Event Simulation ◽  
Decision Making Processes

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.

Discrete-event simulation and agent-based modeling in the tasks of the school informatics course

2020 ◽  
Vol 1 (9) ◽  
pp. 4-13
Author(s):  
N. V. Klimina ◽  
I. A. Morozov
Keyword(s):  
Extracurricular Activities ◽  
Discrete Event ◽  
Simulation Models ◽  
Agent Based Modeling ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Event Simulation ◽  
Cellular Environment ◽  
Scope Of Application ◽  
Biological Simulation

In order to study processes and phenomena, it is necessary to create their models. The most interesting and valuable for the analysis of current situations are models that describe processes as if they were happening in reality. These are the so-called simulation models. The scope of application of simulation models is extensive. The most in demand are economic, sociological and biological simulation models. The relevance of simulation is obvious, and it is natural that the theme of simulation is present in the content of the school informatics course. The article provides guidelines for studying the basics of modeling in a school informatics course related to the creation and research of discrete-event and agent-based simulation models. Examples of tasks recommended for consideration in the 9–11th grades at informatics lessons or in extracurricular activities are given, these are task based on the information-cybernetic approach, implemented in the PascalABC environment, and the task using a cellular automaton, implemented in the Cellular environment.

Simulation of management systems of forest infrastructure

2015 ◽  
Vol 5 (2) ◽  
pp. 177-187
Author(s):  
Васильев ◽  
Oleg Vasilyev ◽  
Корныльева ◽  
Yuliya Kornylyeva
Keyword(s):  
System Dynamics ◽  
Discrete Event Simulation ◽  
Input Data ◽  
Discrete Event ◽  
Agent Based Modeling ◽  
Management Systems ◽  
Center Problem ◽  
Management Tools ◽  
Agent Based ◽  
Event Simulation

The article considers the possibility of a modern and rapidly developing management tools – simulation, allows to obtain detailed statistics on various aspects of the system, depending on the input data. The basic modeling approaches: system dynamics, discrete-event simulation, and agent-based modeling. Forestry breeding and seed center problem to be solved with the help of simulation are substantiated. Examples of problems in other areas of forestry, which can be solved with the help of this tool, are given.

EVALUATION OF SIMULATION TECHNIQUES FOR MODELING PROGRESSION OF CONSTRUCTION CLAIMS

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Mohammad Barakat ◽  
Hiam Khoury ◽  
Mohamed-Asem Abdul-Malak
Keyword(s):  
Construction Projects ◽  
Discrete Event ◽  
Hybrid Approach ◽  
Simulation Models ◽  
Complex Problem ◽  
Weak Links ◽  
Agent Based ◽  
Event Simulation ◽  
Simulation Techniques ◽  
Potential Applicability

The unstructured and dynamic nature of construction projects and the on-site work complexities have been inevitably leading to claims. These evolve according to a staged mechanism set forth in the adopted conditions of contracts. More specifically, claims might progress expeditiously or drag depending on the nature of the applied mechanism and the behavior and interaction among contractual parties. As such, this complex problem of claim progression, which entails a lot of parameters and variables, is addressed in detail in this paper by resorting to three simulation techniques namely: (1) Discrete-Event Simulation (DES), (2) Agent-Based Modeling (ABM), and (3) System Dynamics (SD). The purpose behind this study is two-fold: (1) capturing and visualizing, through three different simulation models, the dynamic and interaction among the different entities as claims are progressing and defining the weak links hindering the efficiency improvement of such a process, and (2) comparing DES, ABM, and SD simulation approaches, using choose-by-advantage technique, and evaluating the advantages and drawbacks of each when studying the progression of claims. Results of all approaches are presented and analyzed followed by a discussion of the effectiveness of each simulation technique and the potential applicability of a hybrid approach in modeling the progression of claims.

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