AgentAllocator: An Agent-Based Multi-criteria Decision Support System for Task Allocation

Matsatsinis, Nikolaos F.; Delias, Pavlos

doi:10.1007/978-3-540-45185-3_21

Cited by 12 publications

(5 citation statements)

References 9 publications

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“…VM process will be facilitated by the implementation of an agent system and it will help to reduce cost and to improve value of building system decision in construction projects. It will also bridge the gap between automated design which were identified earlier by Anumba, et al (2002), Kim & Russel (2003), Halfawy (1998), Khedro (1994), Ugwu et al (1999) on the construction domain in relation to automated negotiation (Matsatsinis & Delias, 2003;Morge & Beaune, 2004;Wanyama, 2006;Wanyama & Far, 2007;Vo & Padgham, 2007) in Information Technology (IT) domain. This significance of the framework is illustrated in Figure 1.…”

Section: The Requirements Of Negotiation Support For Vmmentioning

confidence: 84%

“…This research provides basic and conceptual algorithms to bridge automated design decision, and automated negotiation by applying a systematical design method in construction, that is, VM. Matsatsinis and Delias (2003), Morge and Baune (2004), Wanyama (2006), Wanyama and Far (2007) DESIGN Anumba et al (2002), Kim and Russel (2003), Halfawy (1998), Kedro (1994), Ugwu et al (1999) Limitation Alternatives Design…”

Section: Resultsmentioning

confidence: 99%

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A Concept toward Negotiation Support for Value Management on Sustainable Construction

Utomo¹,

Idrus²

2011

JSD

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Decision making for value-based design in Value Management (VM) is very complicated due to the involvement of many parties. In such situation where the designer, project manager, facility manager and others are involved in choosing a single alternative from a set of solutions, a negotiation support is required to evaluate and rank the solution before engaging into negotiation. This paper presents a conceptual model of negotiation support for VM. It consists of developing the appropriate research approach, methodology of negotiation and agent-based negotiation in VM. The research objectives are to find a theoretical basis and research approach for negotiation support methodology on VM, to develop a decision model for technical solution options in a satisfying function/cost preferences, to investigate negotiation style and outcome and analyze the correlation between them for the basis of scenarios on the agent system, to develop a model for agreement options and coalition algorithms on value-based decision, to validate the coalition algorithms and introduce an initial model of Negotiation Support for Value Management (NSVM). A triangulation methodology has been used to fulfill the objectives. It combines simultaneous triangulation by using case studies and survey methods and sequential triangulation in which results of one method are essential in planning the next method (theoretical mapping, survey research, focus group, case study and conceptual modeling). The methodology is based on a theoretical approach which consists of value-based decision nature in construction VM, multicriteria group decision making, game theory, negotiation theory, and agent-based development. This methodology combines value analysis method using Function Analysis System Technique (FAST); Life Cycle Cost analysis, group decision analysis method based on Analytical Hierarchy Process (AHP), and Game theory-based agent system to develop a negotiation support. The negotiation support bridges theoretical gap between automated design in construction domain and automated negotiation in information technology domain by providing a structured methodology which can lead to systematic support system and automated negotiation for VM process. It will contribute to the Value Management body of knowledge as an advanced method for creativity and analysis phase, since the practice of this knowledge is teamwork based.

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Section: The Requirements Of Negotiation Support For Vmmentioning

confidence: 84%

Section: Resultsmentioning

confidence: 99%

A Concept toward Negotiation Support for Value Management on Sustainable Construction

Utomo¹,

Idrus²

2011

JSD

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“…The aggregation of the evaluation scores for all subcriteria in a particular criterion is based on a simple averaging calculation pro- (Matsatsinis & Delias, 2003). At the end, for a particular combination of product -user features, an average evaluation score in the interval [0, 1] is calculated for every one of the previous four main criteria.…”

Section: Formal Model Alternatives' Performance On Evaluation Criteriamentioning

confidence: 99%

Innovation Management Software Exploiting Multiple Criteria Analysis

Matsatsinis

Grigoroudis

Delias

et al. 2012

International Journal of Decision Support System Technology

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Innovation is a critical factor in building an organization’s culture of growth. Provided that it is properly blended with organizational development initiatives and aligned with the organization’s strategy, it supplies a compelling advantage for the growth process. Neglecting to encompass innovation in an organization’s culture could lead to shrinkage and even extinction, in the case of an intensively competitive market. Executive staff must consider innovative technologies and be aware of all growth opportunities. However, this staff is stressed under information overload. A need exists to reduce the information load and filter available technologies according to the specific needs of the organization. In this paper, the authors propose a recommendation approach to match the needs of an organization against existing technologies (innovative products or services). The organization expresses its customized needs by declaring its preferences over a small reference set of indicative technologies. Each technology is characterized by multiple attributes, in a way that the organization ultimately expresses the trade-offs between the attributes’ significance weights. This information is used to create the organization’s profile. The profile guides a recommendation process, according to which available technologies are evaluated against the profile and proposed to the organization in a descending order.

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“…However, the minimizer of a CSP may not be a Pareto point. There also exist other scalarization methods, such as the ǫ-constraint method [1,37], the lexicographic method [7,22]. We refer to [6,10,36,38,51] for different scalarizations.…”

Section: Introductionmentioning

confidence: 99%

The Multi-Objective Polynomial Optimization

Nie,

Yang

2021

Preprint

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The multi-objective optimization is to optimize several objective functions over a common feasible set. Since the objectives usually do not share a common optimizer, people often consider (weakly) Pareto points. This paper studies multi-objective optimization problems that are given by polynomial functions. First, we study the convex geometry for (weakly) Pareto values and give a convex representation for them. Linear scalarization problems (LSPs) and Chebyshev scalarization problems (CSPs) are typical approaches for getting (weakly) Pareto points. For LSPs, we show how to use tight relaxations to solve them, how to detect existence or nonexistence of proper weights. For CSPs, we show how to solve them by moment relaxations. Moreover, we show how to check if a given point is a (weakly) Pareto point or not and how to detect existence or nonexistence of (weakly) Pareto points. We also study how to detect unboundedness of polynomial optimization, which is used to detect nonexistence of proper weights or (weakly) Pareto points.

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AgentAllocator: An Agent-Based Multi-criteria Decision Support System for Task Allocation

Cited by 12 publications

References 9 publications

A Concept toward Negotiation Support for Value Management on Sustainable Construction

A Concept toward Negotiation Support for Value Management on Sustainable Construction

Innovation Management Software Exploiting Multiple Criteria Analysis

The Multi-Objective Polynomial Optimization

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