scholarly journals A Two-Stage Auction Mechanism for 3PL Supplier Selection under Risk Aversion

2021 ◽  
Vol 13 (17) ◽  
pp. 9745
Author(s):  
Fuqiang Lu ◽  
Hualing Bi ◽  
Yanli Hu ◽  
Wenjing Feng ◽  
Suxin Wang ◽  
...  
Keyword(s):  
Incomplete Information ◽  
Scoring Function ◽  
Complete Information ◽  
Third Party ◽  
Two Stage ◽  
Auction Mechanism ◽  
The Third Party Logistics ◽  
Attribute Weights ◽  
Sustainable Operation ◽  
Fourth Party Logistics

The third party logistics (3PL) suppliers selection is a key issue in sustainable operation of fourth party logistics (4PL). A two-stage auction mechanism is designed for the selection of 3PL suppliers. Different from previous studies, the paper considers risk preference of 4PL integrators during the auction and uses the prospect theory to establish the auction scoring function of 4PL integrators. First, a first score sealed auction (FSSA) mechanism is used to solve the selection problem. However, the results show that FSSA is not an ideal method. Hence, the English auction (EA) mechanism is combined with the FSSA mechanism to form a two-stage auction. The FSSA is taken as the first stage auction, and the EA is taken as the second stage auction, and the two-stage auction mechanism is constructed. The two-stage auction can improve the utility of the 4PL integrator and the auction efficiency. In addition, for the degree of disclosure of attribute weights in the scoring function, two states, complete information and incomplete information is designed. In case analysis, the validity of the designed two-stage auction mechanism is verified. The 4PL integrator can obtain higher utility under the risk-neutral auction than the risk-averse auction. The complete information auction does not make the 4PL integrator obtain higher utility than the incomplete information auction.

scholarly journals Spillovers and R&D Incentive under Incomplete Information

2018 ◽  
Vol 6 (1-2) ◽  
pp. 50-65 ◽  
Author(s):  
Rittwik Chatterjee ◽  
Srobonti Chattopadhyay ◽  
Tarun Kabiraj
Keyword(s):  
Distribution Function ◽  
Incomplete Information ◽  
Private Information ◽  
Complete Information ◽  
Jel Classification ◽  
General Distribution ◽  
Two Stage ◽  
Stage Game ◽  
Alternative Scenarios

Spillovers of R&D outcome affect the R&D decision of a firm. The present paper discusses the R&D incentives of a firm when the extent of R&D spillover is private information to each firm. We construct a two-stage game involving two firms when the firms first decide simultaneously whether to invest in R&D or not, then they compete in quantity. Assuming general distribution function of firm types we compare R&D incentives of firms under alternative scenarios based on different informational structures. The paper shows that while R&D spillovers reduce R&D incentives under complete information unambiguously, however, it can be larger under incomplete information. JEL Classification: D43, D82, L13, O31

The Research of Supply Chain Based on Fourth Party Logistics Optimization

2012 ◽  
Vol 461 ◽  
pp. 393-397 ◽  
Author(s):  
Wen Li ◽  
Meng Yun Wu ◽  
Qiang Mei
Keyword(s):  
Supply Chain ◽  
Rapid Development ◽  
Economic Globalization ◽  
Third Party ◽  
Third Party Logistics ◽  
The Third Party Logistics ◽  
The Third ◽  
Management Ability ◽  
Fourth Party Logistics ◽  
Traditional Competition

With the economic globalization and the rapid development of high-technology, the traditional competition between enterprises has gradually evolved into the competition between the supply chains. It is described the structure models of supply chain and problems existing in the supply chain management, focuses on the comparison between the fourth party logistics and the third party logistics, based on the excellent management ability of the fourth party logistics and its ability to plan and design the supply chain. It is studied how to optimize supply chain through the fourth party logistics in the paper.

scholarly journals TWO-STAGE THIRD-PARTY REVIEW PROPOSAL USING THE ENTERPRISE ARCHITECTURE IN SOFTWARE DEVELOPMENT

2018 ◽  
Vol 126 ◽  
pp. 1187-1196 ◽  
Author(s):  
Haruhiro Tsuchiya ◽  
Shuichiro Yamamoto ◽  
Yuko Murakami ◽  
Tomoyuki Yanagisawa ◽  
Naoko Kobayashi ◽  
...  
Keyword(s):  
Software Development ◽  
Enterprise Architecture ◽  
Third Party ◽  
Two Stage

A Blockchain-Based Two-Stage Secure Spectrum Intelligent Sensing and Sharing Auction Mechanism

2021 ◽  
pp. 1-1
Author(s):  
Rongbo Zhu ◽  
Hao Liu ◽  
Lu Liu ◽  
Xiaozhu Liu ◽  
Wenjie Hu ◽  
...  
Keyword(s):  
Two Stage ◽  
Auction Mechanism

Local Graph Edge Partitioning

2021 ◽  
Vol 12 (5) ◽  
pp. 1-25
Author(s):  
Shengwei Ji ◽  
Chenyang Bu ◽  
Lei Li ◽  
Xindong Wu
Keyword(s):  
Real World ◽  
Graph Partitioning ◽  
Large Scale ◽  
Complete Information ◽  
Local Information ◽  
Experimental Results ◽  
Two Stage ◽  
Graph Computation ◽  
Local Graph ◽  
Edge Partitioning

Graph edge partitioning, which is essential for the efficiency of distributed graph computation systems, divides a graph into several balanced partitions within a given size to minimize the number of vertices to be cut. Existing graph partitioning models can be classified into two categories: offline and streaming graph partitioning models. The former requires global graph information during the partitioning, which is expensive in terms of time and memory for large-scale graphs. The latter creates partitions based solely on the received graph information. However, the streaming model may result in a lower partitioning quality compared with the offline model. Therefore, this study introduces a Local Graph Edge Partitioning model, which considers only the local information (i.e., a portion of a graph instead of the entire graph) during the partitioning. Considering only the local graph information is meaningful because acquiring complete information for large-scale graphs is expensive. Based on the Local Graph Edge Partitioning model, two local graph edge partitioning algorithms—Two-stage Local Partitioning and Adaptive Local Partitioning—are given. Experimental results obtained on 14 real-world graphs demonstrate that the proposed algorithms outperform rival algorithms in most tested cases. Furthermore, the proposed algorithms are proven to significantly improve the efficiency of the real graph computation system GraphX.

scholarly journals Distance Metrics of D Numbers

2020 ◽  
Author(s):  
Liguo Fei ◽  
Yuqiang Feng
Keyword(s):  
Number Theory ◽  
Incomplete Information ◽  
Distance Function ◽  
Distance Measure ◽  
Complete Information ◽  
Belief Function ◽  
Distance Metrics ◽  
Modeling Methods ◽  
The Difference ◽  
D Numbers

Belief function has always played an indispensable role in modeling cognitive uncertainty. As an inherited version, the theory of D numbers has been proposed and developed in a more efficient and robust way. Within the framework of D number theory, two more generalized properties are extended: (1) the elements in the frame of discernment (FOD) of D numbers do not required to be mutually exclusive strictly; (2) the completeness constraint is released. The investigation shows that the distance function is very significant in measuring the difference between two D numbers, especially in information fusion and decision. Modeling methods of uncertainty that incorporate D numbers have become increasingly popular, however, very few approaches have tackled the challenges of distance metrics. In this study, the distance measure of two D numbers is presented in cases, including complete information, incomplete information, and non-exclusive elements

scholarly journals Two-Stage Pursuit Strategy for Incomplete-Information Impulsive Space Pursuit-Evasion Mission Using Reinforcement Learning

Aerospace ◽  
2021 ◽  
Vol 8 (10) ◽  
pp. 299
Author(s):  
Bin Yang ◽  
Pengxuan Liu ◽  
Jinglang Feng ◽  
Shuang Li
Keyword(s):  
Reinforcement Learning ◽  
Incomplete Information ◽  
Trajectory Optimization ◽  
Game Problem ◽  
Gradient Algorithm ◽  
Two Stage ◽  
Pursuit Evasion ◽  
Evasion Game ◽  
Close Distance ◽  
Pursuit Strategy

This paper presents a novel and robust two-stage pursuit strategy for the incomplete-information impulsive space pursuit-evasion missions considering the J2 perturbation. The strategy firstly models the impulsive pursuit-evasion game problem into a far-distance rendezvous stage and a close-distance game stage according to the perception range of the evader. For the far-distance rendezvous stage, it is transformed into a rendezvous trajectory optimization problem and a new objective function is proposed to obtain the pursuit trajectory with the optimal terminal pursuit capability. For the close-distance game stage, a closed-loop pursuit approach is proposed using one of the reinforcement learning algorithms, i.e., the deep deterministic policy gradient algorithm, to solve and update the pursuit trajectory for the incomplete-information impulsive pursuit-evasion missions. The feasibility of this novel strategy and its robustness to different initial states of the pursuer and evader and to the evasion strategies are demonstrated for the sun-synchronous orbit pursuit-evasion game scenarios. The results of the Monte Carlo tests show that the successful pursuit ratio of the proposed method is over 91% for all the given scenarios.

Sign in / Sign up

Export Citation Format

Share Document