Books and journals Case studies Expert Briefings Open Access
Advanced search

Search results

1 – 10 of over 2000
To view the access options for this content please click here
Article
Publication date: 15 March 2011

Constraint priority scheduling using an agent‐based approach

C.Y. Lam and W.H. Ip

Scheduling needs to be concise and well‐determined but able to respond to the ever‐changing and uncertain market or environment against the constraints of production…

HTML
PDF (189 KB)

Abstract

Purpose

Scheduling needs to be concise and well‐determined but able to respond to the ever‐changing and uncertain market or environment against the constraints of production capacity, resources, time frame, etc. The purpose of this paper is to model and solve a scheduling problem with another domain perspective that adopts the concept of agent, and an agent‐based scheduling environment is proposed for solving the scheduling problem, in which three agents are developed, i.e. a sales agent, a scheduling agent, and a production agent.

Design/methodology/approach

The modeling and development of the proposed agent‐based scheduling environment and its agents under constraints are discussed. Constraint priority scheduling concepts are applied to the environment and its agents, and the feature of responding to customer change orders is included in the model. The proposed agent‐based scheduling environment with three agents is applied to a lamp‐manufacturing company in China as a case study, and the integrated agent‐based approach is also illustrated in the case study.

Findings

Throughout the autonomous communication between agents in the proposed model, a constraint‐prioritized schedule is generated to fulfill customer orders and customer change orders, as well as to achieve a better scheduling performance result. From the simulation results and analysis in the case study, satisfactory results show that the proposed model can generate a constraint‐prioritized schedule for the studied company that can completely fulfill customer orders, adjust and fulfill customer change orders, and achieve a better scheduling result.

Originality/value

In this paper, the scheduling problem is modeled and solved by using the domain perspective of agent‐based approach. By using an agent‐based approach, the agents can be implemented to represent manufacturing resources or aggregations of resources. Under the proposed modeling approach, the collaboration across the entire scheduling activities can be enhanced, and the efficiency and effectiveness in the scheduling activities can also be increased.

Details

Industrial Management & Data Systems, vol. 111 no. 2
Type: Research Article
DOI: https://doi.org/10.1108/02635571111115164
ISSN: 0263-5577

Keywords

  • Production scheduling
  • Simulation
  • Manufacturing systems
  • Productivity rate
  • Competitive strategy

To view the access options for this content please click here
Article
Publication date: 14 March 2016

Developing service supply chains by using agent based simulation

Javad Rouzafzoon and Petri Helo

Agent-based computer simulation gives new possibilities to model service supply chains which combine flow of people, geographical elements, demand patterns and service…

HTML
PDF (1.4 MB)

Abstract

Purpose

Agent-based computer simulation gives new possibilities to model service supply chains which combine flow of people, geographical elements, demand patterns and service rates. The purpose of this paper is to demonstrate by using an example how agent-based modeling can be used for health service supply chain design.

Design/methodology/approach

Generic structure of agent-based service supply chain modeling is described. The presented example is healthcare supply chain with service distribution and service location problem. Main focus in presentation on model building, actual case data are not discussed.

Findings

In context of service supply chain, agent-based modeling has advantages compared to traditional discrete event approach. Agent-based simulation allows modeling of interactions of autonomous agents.

Practical implications

Reach of service for each geographical area may be used as a constraint for building service distribution network. Service supply chains consist of service providers and flow of customers with given geographical locations. Key performance indicators can be assessed in combination with service footprint.

Originality/value

Availability of geographical population data and agent-based simulation gives new possibility for service supply chain models.

Details

Industrial Management & Data Systems, vol. 116 no. 2
Type: Research Article
DOI: https://doi.org/10.1108/IMDS-05-2015-0220
ISSN: 0263-5577

Keywords

  • Simulation
  • Agent-based modelling
  • Service supply chain

To view the access options for this content please click here
Article
Publication date: 13 March 2017

Agent-based modeling of availability for complex multiple units systems

Ling Wang, Hong Xu, Jinjin Wu, Xiai Chen and Wenbo Na

The purpose of this paper is to propose an availability modeling method of complex multiple units system (CMUS) based on the multi-agent technique.

HTML
PDF (479 KB)

Abstract

Purpose

The purpose of this paper is to propose an availability modeling method of complex multiple units system (CMUS) based on the multi-agent technique.

Design/methodology/approach

Based on the multi-agent technique, this paper describes the availability model structure for CMUS and develops agent-based models of components, maintenance policies, maintenance tools, maintenance fields, and maintenance staff, as well as the communication method among the different agents. On the basis of the agent-based availability modeling theory, the availability simulation scheme of CMUS is given using MATLAB. Thus, the availability modeling theory of CMUS and its simulation method are developed. To demonstrate the applicability of the proposed availability modeling method, a numerical example is given.

Findings

The proposed agent-based modeling method is applicable to availability modeling of CMUS, including the modeling of component failure, maintenance tools/fields/staff, maintenance policy, and structural/economic dependence among components.

Practical implications

As a bottom-top, modular, expandable, and reusable modeling theory, the agent-based modeling method might be useful for availability modeling of different CMUSs in reality.

Originality/value

The multi-agent technique is introduced into availability modeling of multi-component systems in this paper. Thus, it is possible to model failure of many components, maintenance policies, maintenance tools, maintenance fields, and maintenance staff together for availability analysis of complex systems of equipment.

Details

Journal of Quality in Maintenance Engineering, vol. 23 no. 1
Type: Research Article
DOI: https://doi.org/10.1108/JQME-06-2013-0033
ISSN: 1355-2511

Keywords

  • Availability modelling
  • Agent-based component model
  • Agent-based maintenance policy model
  • Complex multiple units system
  • Multi-agent modelling

Content available
Article
Publication date: 2 December 2019

Agent-based modelling and economic complexity: a diversified perspective

Christophe Schinckus

The term “agent-based modelling” (ABM) is a buzzword which is widely used in the scientific literature even though it refers to a variety of methodologies implemented in…

Open Access
HTML
PDF (432 KB)

Abstract

Purpose

The term “agent-based modelling” (ABM) is a buzzword which is widely used in the scientific literature even though it refers to a variety of methodologies implemented in different disciplinary contexts. The numerous works dealing with ABM require a clarification to better understand the lines of thinking paved by this approach in economics. All modelling tasks are a means and a source of knowledge, and this epistemic function can vary depending on the methodology. this paper is to present four major ways (deductive, abductive, metaphorical and phenomenological) of implementing an agent-based framework to describe economic systems. ABM generates numerous debates in economics and opens the room for epistemological questions about the micro-foundations of macroeconomics; before dealing with this issue, the purpose of this paper is to identify the kind of ABM the author can find in economics.

Design/methodology/approach

The profusion of works dealing with ABM requires a clarification to understand better the lines of thinking paved by this approach in economics. This paper offers a conceptual classification outlining the major trends of ABM in economics.

Findings

There are four categories of ABM in economics.

Originality/value

This paper suggests a methodological categorization of ABM works in economics.

Details

Journal of Asian Business and Economic Studies, vol. 26 no. 2
Type: Research Article
DOI: https://doi.org/10.1108/JABES-12-2018-0108
ISSN: 2515-964X

Keywords

  • Econophysics
  • Economic complexity
  • Agent-based modelling
  • B41
  • C63
  • C89

To view the access options for this content please click here
Article
Publication date: 1 February 2002

Agent‐based modelling of customer behaviour in the telecoms and media markets

Paul Twomey and Richard Cadman

Agent‐based modelling is a bottom‐up approach to understanding systems which provides a powerful tool for analysing complex, non‐linear markets. The method involves…

HTML
PDF (92 KB)

Abstract

Agent‐based modelling is a bottom‐up approach to understanding systems which provides a powerful tool for analysing complex, non‐linear markets. The method involves creating artificial agents designed to mimic the attributes and behaviours of their real‐world counterparts. The system’s macro‐observable properties emerge as a consequence of these attributes and behaviours and the interactions between them. The simulation output may be potentially used for explanatory, exploratory and predictive purposes. The aim of this paper is to introduce the reader to some of the basic concepts and methods behind agent‐based modelling and to present some recent business applications of these tools, including work in the telecoms and media markets.

Details

info, vol. 4 no. 1
Type: Research Article
DOI: https://doi.org/10.1108/14636690210426640
ISSN: 1463-6697

Keywords

  • Modelling
  • Consumer behaviour
  • United Kingdom
  • Telecommunications
  • Broadcasting

To view the access options for this content please click here
Book part
Publication date: 5 October 2018

Fuzzy Simulation Techniques in Construction Engineering and Management

Mohammad Raoufi, Nima Gerami Seresht, Nasir Bedewi Siraj and Aminah Robinson Fayek

Several different simulation techniques, such as discrete event simulation (DES), system dynamics (SD) and agent-based modelling (ABM), have been used to model complex…

HTML
PDF (1.1 MB)
EPUB (649 KB)

Abstract

Several different simulation techniques, such as discrete event simulation (DES), system dynamics (SD) and agent-based modelling (ABM), have been used to model complex construction systems such as construction processes and project management practices; however, these techniques do not take into account the subjective uncertainties that exist in many construction systems. Integrating fuzzy logic with simulation techniques enhances the capabilities of those simulation techniques, and the resultant fuzzy simulation models are then capable of handling subjective uncertainties in complex construction systems. The objectives of this chapter are to show how to integrate fuzzy logic and simulation techniques in construction modelling and to provide methodologies for the development of fuzzy simulation models in construction. In this chapter, an overview of simulation techniques that are used in construction is presented. Next, the advancements that have been made by integrating fuzzy logic and simulation techniques are introduced. Methodologies for developing fuzzy simulation models are then proposed. Finally, the process of selecting a suitable simulation technique for each particular aspect of construction modelling is discussed.

Details

Fuzzy Hybrid Computing in Construction Engineering and Management
Type: Book
DOI: https://doi.org/10.1108/978-1-78743-868-220181004
ISBN: 978-1-78743-868-2

Keywords

  • Fuzzy logic
  • simulation
  • construction
  • agent-based modelling
  • system dynamics
  • discrete event simulation

To view the access options for this content please click here
Article
Publication date: 1 November 2019

Mount Merapi eruption: Simulating dynamic evacuation and volunteer coordination using agent-based modeling approach

Bertha Maya Sopha, Risqika Edni Doni Achsan and Anna Maria Sri Asih

Uneven distribution and mistarget beneficiaries are among problems encountered during post-disaster relief operations in 2010 Mount Merapi eruption. The purpose of this…

HTML
PDF (754 KB)

Abstract

Purpose

Uneven distribution and mistarget beneficiaries are among problems encountered during post-disaster relief operations in 2010 Mount Merapi eruption. The purpose of this paper is to develop an empirically founded agent-based simulation model addressing the evacuation dynamics and to explore coordination mechanism and other promising strategies during last-mile relief delivery.

Design/methodology/approach

An agent-based model which was specified and parameterized by empirical research (interviews and survey) was developed to understand the mechanism of individual decision making underlying the evacuation dynamics. A set of model testing was conducted to evaluate confidence level of the model in representing the evacuation dynamics during post-disaster of 2010 Mount Merapi eruption. Three scenarios of last-mile relief delivery at both strategic and operational levels were examined to evaluate quantitatively the effectiveness of the coordination mechanism and to explore other promising strategies.

Findings

Results indicate that the empirically founded agent-based modeling was able to reproduce the general pattern of observable Internal Displaced Persons based on government records, both at micro and macro levels, with a statistically non-significant difference. Low hazard perception and leader-following behavior which refuses to evacuate are the two factors responsible for late evacuation. Unsurprisingly, coordination through information sharing results in better performance than without coordination. To deal with both uneven distribution and long-term demand fulfillment, coordination among volunteers during aid distribution (at downstream operation) is not sufficient. The downstream coordination should also be accompanied with coordination between aid centers at the upstream operation. Furthermore, the coordination which is combined with other operational strategies, such as clustering strategy, using small-sized trucks and pre-positioning strategy, seems to be promising. It appears that the combined strategy of coordination and clustering strategy performs best among other combined strategies.

Practical implications

The significant role of early evacuation and self-evacuation behavior toward efficient evacuation indicates that human factor (i.e. hazard perception and cultural factor) should be considered in designing evacuation plan. Early warning system through both technology and community empowerment is necessary to support early evacuation. The early warning system should also be accompanied with at least 69 percent of the population performing self-evacuation behavior for the effective evacuation. As information sharing through coordination is necessary to avoid redundant efforts, uneven distribution and eventually to reduce unmet demand, the government can act as a coordinating actor to authorize the operation and mobilize the resources. The combination of coordination and another strategy reducing lead time such as clustering analysis, thus increasing responsiveness, is seemly strategy for efficient and effective last-mile relief distribution.

Originality/value

Literature on coordination is dominated by qualitative approach, which is difficult to evaluate its effectiveness quantitatively. Providing realistic setting of the evacuation dynamics in the course of the 2010 Mount Merapi eruption, the empirically founded agent-based model can be used to understand the factors influencing the evacuation dynamics and subsequently to quantitatively examine coordination mechanisms and other potential strategies toward efficient and effective last-mile relief distribution.

Details

Journal of Humanitarian Logistics and Supply Chain Management, vol. 9 no. 2
Type: Research Article
DOI: https://doi.org/10.1108/JHLSCM-05-2018-0035
ISSN: 2042-6747

Keywords

  • Coordination
  • Agent-based modelling
  • Evacuation decision making
  • Evacuation dynamics
  • Mount Merapi eruption

To view the access options for this content please click here
Article
Publication date: 11 June 2018

Agent-based modeling and simulation of the decision behaviors of e-retailers

Guoyin Jiang, Shan Liu, Wenping Liu and Yan Xu

Social media facilitates consumer exchanges on product opinions and provides comprehensive knowledge of online products. The interaction between consumers and e-retailers…

HTML
PDF (348 KB)

Abstract

Purpose

Social media facilitates consumer exchanges on product opinions and provides comprehensive knowledge of online products. The interaction between consumers and e-retailers evolves into a collective set of dynamics within a complex system. Agent-based modeling is well suited to stimulate such complex systems. The purpose of this paper is to integrate agent-based model and technique for order performance by similarity to ideal solution (TOPSIS) to simulate decision behaviors of e-retailers in competitive online markets.

Design/methodology/approach

An agent-based network model using the TOPSIS driven by actual price data is developed. The authors ran an experimental model to simulate interactions between online consumers and e-retailers and to record simulation data. A nonparametric test is used to conduct data analysis and evaluate the sensibility of parameters.

Findings

Simulation results showed that different profits could be obtained for various brands under different social network structures. E-retailers could achieve more profits through cross-selling than single-selling; however, the highest profits can be achieved when some adopt cross-selling, whereas others use single-selling. From a game perspective, the equilibrium for price-adjustment frequency can be determined from the simulation data. Thus, price adjustment differences significantly affect e-retailer profit.

Originality/value

This study provides new insights into the evolutionary dynamics of online markets. This work also indicates how to build an integrated simulation model with an agent-based model and TOPSIS and how to use an integrated simulation model and interpret its results.

Details

Industrial Management & Data Systems, vol. 118 no. 5
Type: Research Article
DOI: https://doi.org/10.1108/IMDS-07-2017-0321
ISSN: 0263-5577

Keywords

  • TOPSIS
  • E-commerce
  • Cross-selling
  • Agent-based modelling
  • Collective dynamics

To view the access options for this content please click here
Article
Publication date: 11 April 2016

On the contributions and the validation of an agent-based simulation model of innovation diffusion

Mohammad G. Nejad

This paper provides an overview of agent-based modeling and simulation (ABMS) and evaluates the questions that have been raised regarding the “assumptions and mechanisms…

HTML
PDF (104 KB)

Abstract

Purpose

This paper provides an overview of agent-based modeling and simulation (ABMS) and evaluates the questions that have been raised regarding the “assumptions and mechanisms used” by a well-cited paper that has used this methodology.

Design/methodology/approach

This work provides a review of agent-based simulation modeling and its capabilities to advance and test theory. The commentary then evaluates and addresses the raised questions and reservations.

Findings

Agent-based modeling offers unique capabilities that can be used to explore complex phenomena in business and marketing. Some of the raised reservations may be considered as directions for future research. However, the criticisms are for most part unsupported by existing research and do not undermine the contributions of the paper that is being discussed.

Practical implications

Given its relative novelty, reservations regarding agent-based simulation modeling are quite natural. Discussions like this one would bring together different points of view and lead to a better understanding of how using ABMS can benefit academia and industry.

Originality/value

This commentary is part of an intellectual dialogue that seeks to provide different points of view about agent-based simulation modeling using a specific paper as an example.

Details

European Journal of Marketing, vol. 50 no. 3/4
Type: Research Article
DOI: https://doi.org/10.1108/EJM-02-2016-0108
ISSN: 0309-0566

Keywords

  • Agent-based modeling and simulation
  • Innovation diffusion
  • Negative word-of-mouth
  • Research methodology
  • Validation and verification

To view the access options for this content please click here
Article
Publication date: 1 March 2013

Growing artificial entrepreneurs : Advancing entrepreneurship research using agent‐based simulation approach

Shu‐Jung Sunny Yang and Yanto Chandra

The aim of this paper is to offer agent‐based modelling (ABM) as an alternative approach to advance research in entrepreneurship. It argues that ABM allows…

HTML
PDF (295 KB)

Abstract

Purpose

The aim of this paper is to offer agent‐based modelling (ABM) as an alternative approach to advance research in entrepreneurship. It argues that ABM allows entrepreneurship researchers (i.e. the designers) to find better ways in generating entrepreneurial outcomes by understanding alternative histories and examining a plausible future.

Design/methodology/approach

This paper begins with an overview of ABM, and discusses the shared conceptual foundations of entrepreneurship and ABM as the motives for the adoption of ABM as an appropriate methodology to study entrepreneurship. It offers a roadmap in using ABM approach for entrepreneurship research and illustrates this using a contemporary research question in entrepreneurship: the study of success/failure in business venturing.

Findings

This paper suggests the shared foundations between ABM and entrepreneurship as the basis for bringing the methodology and research domain closer. It offers a roadmap for advancing entrepreneurship research using agent‐based simulation approach and explains the contribution of ABM to further advance entrepreneurship research.

Originality/value

This paper addresses the methodological gap in entrepreneurship research and develops the argument for a wider adoption of ABM simulation approach to study entrepreneurship. It bridges the gap by examining the possibility of formalizing entrepreneurship processes by grounding an agent‐based model on empirical facts and generally‐accepted foundations of entrepreneurship. It offers a contribution to the literature by showing that ABM is a useful and appropriate methodological approach for entrepreneurship research in addition to the conventional variance and process approach.

Details

International Journal of Entrepreneurial Behavior & Research, vol. 19 no. 2
Type: Research Article
DOI: https://doi.org/10.1108/13552551311310383
ISSN: 1355-2554

Keywords

  • Entrepreneurship
  • Agent‐based modelling
  • Simulation
  • Effectuation
  • Entrepreneurs
  • Entrepreneurialism

Access
Only content I have access to
Only Open Access
Year
  • Last week (8)
  • Last month (21)
  • Last 3 months (64)
  • Last 6 months (144)
  • Last 12 months (275)
  • All dates (2132)
Content type
  • Article (1683)
  • Book part (317)
  • Earlycite article (124)
  • Case study (8)
1 – 10 of over 2000
Emerald Publishing
  • Opens in new window
  • Opens in new window
  • Opens in new window
  • Opens in new window
© 2021 Emerald Publishing Limited

Services

  • Authors Opens in new window
  • Editors Opens in new window
  • Librarians Opens in new window
  • Researchers Opens in new window
  • Reviewers Opens in new window

About

  • About Emerald Opens in new window
  • Working for Emerald Opens in new window
  • Contact us Opens in new window
  • Publication sitemap

Policies and information

  • Privacy notice
  • Site policies
  • Modern Slavery Act Opens in new window
  • Chair of Trustees governance statement Opens in new window
  • COVID-19 policy Opens in new window
Manage cookies

We’re listening — tell us what you think

  • Something didn’t work…

    Report bugs here

  • All feedback is valuable

    Please share your general feedback

  • Member of Emerald Engage?

    You can join in the discussion by joining the community or logging in here.
    You can also find out more about Emerald Engage.

Join us on our journey

  • Platform update page

    Visit emeraldpublishing.com/platformupdate to discover the latest news and updates

  • Questions & More Information

    Answers to the most commonly asked questions here