Model and algorithm for 4PLRP with uncertain delivery time

Huang, Min; Ren, Liang; Lee, Loo Hay; Wang, Xingwei; Kuang, Hanbin; Shi, Haibo

doi:10.1016/j.ins.2015.10.030

Cited by 35 publications

(15 citation statements)

References 42 publications

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“…For example, an analytical multi-attribute decision making framework was constructed to evaluate the 4PL operating models for a logistics company that is willing to expand its operations [28]. In recent days, to identify the cost-effective ways of increasing the operational efficiency of logistics, a variety of interesting issues have been investigated, such as the routing problem [9, 19, 29, 30] and the network design problem [2, 31–33]. The above models developed so far assumed that the 4PL could have full information during the decision-making process.…”

Section: Literature Reviewmentioning

confidence: 99%

Mechanism design of incentive-based reverse auctions with loss-averse 3PLs under incomplete attributes

et al. 2018

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As a supply chain solution integrator, fourth party logistics (4PL) has become an important focus for improving the operational efficiency of the logistics industry in recent days. This paper addresses the mechanism design problem of the 4PL for selecting a third party logistics (3PL) provider who involves loss-averse behavior to form a longer-term strategic partnership in multi-attribute reverse auctions. Due to fluctuating costs of energy or labor and unintentional delivery failures like traffic jam or technology malfunctions, we consider two incomplete attributes, namely cost uncertainty and delivery risk. Integrating the loss-averse behavior of 3PLs, based on the prospect theory, the bid decision model is constructed to obtain 3PLs’ bidding strategies. The corresponding efficient and optimal scoring auctions that consist of cost-sharing contract and contingent penalty are developed to maximize the ex ante expected profit of the system or the 4PL depending on whether the 4PL is willing to cooperate or not. Theoretical analysis verified by numerical examples illustrates the advantage of the proposed mechanisms. Impacts of model parameters on the 4PL’s decision are also investigated and managerial insights are presented.

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Section: Literature Reviewmentioning

confidence: 99%

Mechanism design of incentive-based reverse auctions with loss-averse 3PLs under incomplete attributes

et al. 2018

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“…In transportation, the uncertainty theory is extensively used in logistics distribution and vehicle scheduling. For example, Huang [20] described the delivery time of a third-party logistics supplier as an uncertain variable, subsequently converted the model into an equivalent deterministic model, and designed several improved genetic algorithms to solve it. Hua [21] used the time of logistics project development activities as an uncertain variable to establish a model, designed an intelligent algorithm based on simulated annealing and conducted a logistics project as an example to illustrate the effectiveness of the model and algorithm.…”

Section: Introductionmentioning

confidence: 99%

Research on Optimization of Customized Bus Routes Based on Uncertainty Theory

Sang

Zhang

Xue

et al. 2021

Journal of Advanced Transportation

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In the optimization process of the routes of customized buses, there are numerous uncertainties in the route planning and setting. In this study, the uncertainty theory is introduced into the optimization problem of a customized bus route, and an uncertain customized bus route optimization model is established, which aims at the minimizing the total mileage of vehicle operation. An improved genetic algorithm is used to solve the model, whose feasibility is verified by a case study. The results show that the optimization model based on the uncertainty theory can yield a reasonable customized bus route optimization scheme, and the total mileage reduced from 35.6 kilometers to 32.2 kilometers. This research provides the theoretical support for the optimization of customized bus routes.

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“…Thus, uncertainty theory is more suitable for situations with limited/scarce data for statistical analysis. It has been introduced to various domains, such as reliability analysis [19] [20], risk analysis [21], supply chain [22], accelerated degradation testing [23], data development analysis [24], etc.…”

Section: Introductionmentioning

confidence: 99%

First-Order Uncertain Hidden Semi-Markov Process for Failure Prognostics With Scarce Data

Liu

2020

IEEE Access

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Failure prognostics aims at predicting the object equipment's future degradation trend and derives the remaining useful life with a predefined failure threshold. Hidden semi-Markov process (HSMP) is widely adopted for failure prognostics of degradation process with discrete states. The effective estimation of the holding time distribution on each degradation state is of critical importance for the prediction performance of a HSMP model. The distributions are generally estimated with frequencies-based probabilities given a large amount of degradation data. In practical engineering applications, it is difficult to collect enough data and the data can even be scarce. In such situations, the estimated distributions are no longer reliable. First-order uncertain hidden semi-Markov process (1-UHSMP) based on uncertain statistics is defined in this work. The holding time distributions in 1-UHSMP are described with uncertainty theory and are adaptively updated with conditional uncertainty distributions given observations related to the true degradation states. Analytical expressions are derived for the expected remaining useful life for 1-UHSMP with regular uncertainty distributions, i.e. normal and linear uncertainty distribution. The proposed method can build a degradation model from scarce data and derive adaptively the remaining useful life with associated uncertainty interval. A case study concerning centrifugal pumps in a nuclear power plant is considered to verify the effectiveness of 1-UHSMP.

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Model and algorithm for 4PLRP with uncertain delivery time

Cited by 35 publications

References 42 publications

Mechanism design of incentive-based reverse auctions with loss-averse 3PLs under incomplete attributes

Mechanism design of incentive-based reverse auctions with loss-averse 3PLs under incomplete attributes

Research on Optimization of Customized Bus Routes Based on Uncertainty Theory

First-Order Uncertain Hidden Semi-Markov Process for Failure Prognostics With Scarce Data

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