Assessment of Resource Allocation and Tradeoff Analysis Approaches in Transportation Asset Management

2018 ◽  
Vol 2672 (44) ◽  
pp. 21-31 ◽  
Author(s):  
James Bryce ◽  
Gonzalo Rada ◽  
Samuel Van Hecke ◽  
Joseph Zissman
Keyword(s):  
Resource Allocation ◽  
Asset Management ◽  
State Agencies ◽  
Multi Objective ◽  
Current State ◽  
Allocation Process ◽  
Transportation Asset Management ◽  
Key Steps ◽  
Transportation Agencies ◽  
Resource Allocation Process

Transportation asset management (TAM) practices continue to grow and to develop as transportation agencies seek to make more objective and defensible decisions, as well as responding to recent legislation. One primary goal of TAM is to provide a structure in which decisions on how to distribute resources across many disparate assets can be made using a systematic process. Resource allocation is analogous to multi-objective optimization, and thus presents the complication that many potential optimal solutions (i.e., a Pareto set) can be found. To solve the multi-objective resource allocation problem, many approaches have been recommended, such as the use of utility theory and weighting functions to express preferences that result in a single solution being selected. This paper discusses those recommendations, as well as describing the current state of the resource allocation process in an effort to identify gaps in practice and, in turn, to provide recommendations for addressing those gaps. First, the process of cross-asset resource allocation is deconstructed to highlight the key steps. Then, current practices identified from the literature, as well as from interviews with five State agencies are discussed. Finally, a set of recommendations for improving resource allocation and the supporting processes within resource allocation are presented.

A resource allocation framework for predisaster resilience management of interdependent infrastructure networks

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jingran Sun ◽  
Srijith Balakrishnan ◽  
Zhanmin Zhang
Keyword(s):  
Resource Allocation ◽  
Extreme Events ◽  
Asset Management ◽  
Agent Based Modeling ◽  
Methodological Framework ◽  
Content Type ◽  
Agent Based ◽  
Allocation Process ◽  
Infrastructure Network ◽  
Resource Allocation Process

PurposeResource allocation is essential to infrastructure management. The purpose of this study is to develop a methodological framework for resource allocation that takes interdependencies among infrastructure systems into consideration to minimize the overall impact of infrastructure network disruptions due to extreme events.Design/methodology/approachTaking advantage of agent-based modeling techniques, the proposed methodology estimates the interdependent effects of a given infrastructure failure which are then used to optimize resource allocation such that the network-level resilience is maximized.FindingsThe findings of the study show that allocating resources with the proposed methodology, where optimal infrastructure reinforcement interventions are implemented, can improve the resilience of infrastructure networks with respect to both direct and interdependent risks of extreme events. These findings are also verified by the results of two case studies.Practical implicationsAs the two case studies have shown, the proposed methodological framework can be applied to the resource allocation process in asset management practices.Social implicationsThe proposed methodology improves the resilience of the infrastructure network, which can alleviate the social and economic impact of extreme events on communities.Originality/valueCapitalizing on the combination of agent-based modeling and simulation-based optimization techniques, this study fulfills a critical gap in infrastructure asset management by incorporating infrastructure interdependence and resilience concepts into the resource allocation process.

scholarly journals Recommendation with Diversity: Mass Diffusion Model Based on Trust Network and Object Reputation

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yun Bai ◽  
Wandong Cai
Keyword(s):  
Resource Allocation ◽  
Diffusion Model ◽  
Recommendation System ◽  
Small Degree ◽  
Mass Diffusion ◽  
Recommendation Algorithm ◽  
Trust Relationship ◽  
Positive Effects ◽  
Allocation Process ◽  
Resource Allocation Process

The traditional mass diffusion recommendation algorithm only relies on the user’s object collection relationship, resulting in poor recommendation performance for users with small purchases (i.e., small-degree user), and it is difficult to balance the accuracy and diversity of the recommendation system. This paper introduces the trust relationship into the resource allocation process of the traditional mass diffusion algorithm and proposes the Dual Wing Mass Diffusion model (DWMD), which constructs a dual wing graph based on trust relationships and object collection relationships. Implicit trust is mined according to the network structure of the trust relationship and integrated into the resource allocation process, and then merging the positive effects of object reputation on a recommendation through tunable scaling parameters. The user controls the tunable scaling parameter to achieve the best recommendation performance. The experimental results show that the DWMD method significantly improves diversity and novelty while ensuring high accuracy and effectively improves the accuracy and diversity balance. The improved recommendation performance for small-degree users proves that the trust relationship can effectively alleviate the generalized cold start problem of the recommendation algorithm for users who collect a small number of objects.

The Resource Allocation Process

2018 ◽  
pp. 79-93
Author(s):  
Richard Busulwa ◽  
Matthew Tice ◽  
Bruce Gurd
Keyword(s):  
Resource Allocation ◽  
Allocation Process ◽  
Resource Allocation Process

A Stochastic Decentralized Resource Allocation Process: Part II

Econometrica ◽  
1975 ◽  
Vol 43 (3) ◽  
pp. 363 ◽  
Author(s):  
Leonid Hurwicz ◽  
Roy Radner ◽  
Stanley Reiter
Keyword(s):  
Resource Allocation ◽  
Allocation Process ◽  
Decentralized Resource Allocation ◽  
Resource Allocation Process

Research on Multi-Project Resource Allocation Process and Application

2013 ◽  
Vol 357-360 ◽  
pp. 2267-2272
Author(s):  
Xin Li Zhang ◽  
Jie Li ◽  
Yan Fang Zhu
Keyword(s):  
Resource Allocation ◽  
Allocation Problem ◽  
Resource Allocation Problem ◽  
Interactive Process ◽  
Allocation Process ◽  
Fixed Period ◽  
Resource Allocation Process

Based on the existing research on multi-project resource allocation, this research presents the triangle relationship diagram about the objective, constraints, and algorithm during project resource allocation; and designs the interactive process for multi-project resource allocation, which combines the project objective, constraint, and algorithm. In addition, a case about fixed period - fixed resources problem is solved to verify the feasibility of the interactive process; the research develops the comprehensive concept for project resource allocation problem.

The Influence of Managerial Orientation in Decision-Making Processes

ACCRUALS ◽  
2020 ◽  
Vol 4 (01) ◽  
pp. 1-8
Author(s):  
Rusdianto Rusdianto
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Stakeholder Theory ◽  
Resource Availability ◽  
Individual Level ◽  
Allocation Process ◽  
Resources Distribution ◽  
Decision Making Processes ◽  
The Individual ◽  
Resource Allocation Process

This research aims to examine managerial preferences in the resource allocation process. This research used an experimental method to test whether resource availability, stakeholder claims, and managers’ affiliations to stockholders can influence the decision-making process of resource allocation. The results show that resource availability, stakeholder claims, and managers’ affiliation could influence the resource allocation process. The results of the research contribute to several things. The first is to show that stakeholder theory can test managerial preferences at the individual level. Secondly, the resources distribution is influenced by behavioral factors associated with normative stakeholder theory.

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