Mechanism Design for Stochastic Dynamic Parking Resource Allocation

2021 ◽  
Author(s):  
Jie Yang ◽  
Fang He ◽  
Xi Lin ◽  
Max Zuo‐jun Shen
Keyword(s):  
Resource Allocation ◽  
Mechanism Design ◽  
Stochastic Dynamic

Mechanism Design for Online Resource Allocation

2020 ◽  
Vol 48 (1) ◽  
pp. 11-12
Author(s):  
Xiaoqi Tan ◽  
Bo Sun ◽  
Alberto Leon-Garcia ◽  
Yuan Wu ◽  
Danny H.K. Tsang
Keyword(s):  
Resource Allocation ◽  
Mechanism Design ◽  
Online Resource

scholarly journals Analysing Istanbul Strait Maritime Pilot Capacity by Simulation Technique

2015 ◽  
Vol 69 (4) ◽  
pp. 815-827 ◽  
Author(s):  
Emre Ucan ◽  
Selcuk Nas
Keyword(s):  
Resource Allocation ◽  
Simulation Software ◽  
Simulation Technique ◽  
Stochastic Dynamic ◽  
Simulation Experiments ◽  
Discrete Simulation ◽  
Service Allocation ◽  
Stochastic Problems ◽  
Allocation Problems ◽  
Service Standards

Nautical services should be allocated efficiently as they have great resource costs. In this paper, the Marine Pilotage Service in the Istanbul Strait has been analysed by using Rockwell Arena Simulation Software. The purpose of the study is to find the required number of marine pilots for vessel traffic flow in the Istanbul Strait. It is evaluated thoroughly by a stochastic, dynamic, discrete simulation for safe service standards in pilotage. The result of the paper shows that discrete simulation technique is an efficient and reliable way of solving complex techno-nautical service allocation problems as proven by experts. As the discrete simulation result data shows, most other techno-nautical services can also be modelled and optimised by using similar techniques. Areas like optimisation of the number of pilots, tugs, resource allocation problems, berthing area selections and many more complex and inherently stochastic problems can be reliably solved by simulation experiments.

scholarly journals PeerNomination: Relaxing Exactness for Increased Accuracy in Peer Selection

2020 ◽  
Author(s):  
Nicholas Mattei ◽  
Paolo Turrini ◽  
Stanislav Zhydkov
Keyword(s):  
Artificial Intelligence ◽  
Resource Allocation ◽  
Theoretical Analysis ◽  
Mechanism Design ◽  
Individual Agent ◽  
Broad Application ◽  
Peer Selection ◽  
Design Algorithms ◽  
Novel Algorithm

In peer selection agents must choose a subset of themselves for an award or a prize. As agents are self-interested, we want to design algorithms that are impartial, so that an individual agent cannot affect their own chance of being selected. This problem has broad application in resource allocation and mechanism design and has received substantial attention in the artificial intelligence literature. Here, we present a novel algorithm for impartial peer selection, PeerNomination, and provide a theoretical analysis of its accuracy. Our algorithm possesses various desirable features. In particular, it does not require an explicit partitioning of the agents, as previous algorithms in the literature. We show empirically that it achieves higher accuracy than the exiting algorithms over several metrics.

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