Optimization of facility location and size problem based on bi-level multi-objective programming

Hu, Zhineng; Wang, Li; Qin, Jindong; Lev, Benjamin; Gan, Lu

doi:10.1016/j.cor.2022.105860

Cited by 17 publications

(2 citation statements)

References 46 publications

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“…Multi-objective programming can provide Pareto-optimal solutions at each level, but the more critical problem is to obtain the optimal solution for lower-level optimization. Bonnel et al (2015) and Hu et al (2022) provided the optimal solution for the leader and follower under optimistic and pessimistic conditions. These optimistic and pessimistic approaches are significant as well in dealing with our MBO.…”

Section: Bilevel Optimization Under Amentioning

confidence: 99%

Two‐sided networks coordination for manufacturing technology standards' diffusion from home to host countries: A one‐leader and multiple‐followers Stackelberg game with multiple objectives

Zhou,

Wu,

Chen

et al. 2024

Manage Decis Econ

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An optimization model is necessary to depict and induce the volatility and irregularity of manufacturing technology standard (MTS) diffusion processes to ensure that the standard can be widely adopted by related stakeholders in host countries. This paper clarifies the two‐sided network coordination of MTS's transactional diffusion, consisting of new product diffusion among users and new technology diffusion among local suppliers. A procurement contract is introduced to connect and coordinate the two‐sided networks. The manufacturer from the home country is responsible for the contract design, which aims to maximize its net revenue by considering the product diffusion processes. Local suppliers determine whether to accept the contract. The decision‐making objectives of the contract acceptance for each local supplier are to maximize the net revenue and minimize workload fluctuation. The new standard‐based products are produced and sold by the manufacturer. The corresponding local supplier adopts new standard‐based technologies and supplies components for final product production if a contract is accepted. Therefore, a one‐leader and multiple‐follower Stackelberg game is proposed to figure out the best solution after coordinating the multiple objectives of each participant. The contract design and the contract acceptance are the leader and the follower, respectively. Analytical solutions under a specific MTS for refrigerator production are developed incorporating a nested Non‐dominated Sorting Genetic Algorithm‐II. The results demonstrate that the proposed method can efficiently coordinate the two‐sided networks of MTS diffusion and balance the net revenue of all related stakeholders.

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Section: Bilevel Optimization Under Amentioning

confidence: 99%

Two‐sided networks coordination for manufacturing technology standards' diffusion from home to host countries: A one‐leader and multiple‐followers Stackelberg game with multiple objectives

Zhou,

Wu,

Chen

et al. 2024

Manage Decis Econ

View full text Add to dashboard Cite

show abstract

“…Ge et al examined the facility location problem for the U.S. fresh produce supply chain by adopting complementary modeling approaches [35]. Hu et al developed a bi-level multi-objective model to optimize the location and size of general service infrastructure in urban areas [36]. Wolff et al developed a mathematical model to determine the optimal locations of transport infrastructure, a question which is related to the design of renewable fuel supply chains [37].…”

Section: Facility Locationmentioning

confidence: 99%

Optimizing the Location of Virtual-Shopping-Experience Stores Based on the Minimum Impact on Urban Traffic

Wang

2023

Sustainability

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In order to enhance consumers’ experience of online shopping and to reduce their unnecessary car trips for offline shopping, a new mode, namely, establishing the virtual-shopping-experience store, is proposed in this paper. A bi-level programming model is then built with the aim of optimizing the location of the virtual-shopping-experience stores. The upper-level submodel is utilized to optimize the location of the experience stores, as well as the selection of virtual-reality (VR) devices purchased by the stores, by maximizing the social welfare generated from reducing the car trips for offline shopping after the establishment of the virtual-shopping-experience stores. The lower-level submodel is a binary Logit model, one which calculates the probability of consumers’ choices between online and offline shopping according to the locations of the experience stores output by the upper-level submodel. A genetic algorithm is adopted to solve the model. To validate the accuracy of the model, as well as that of the algorithm, case studies are carried out based on the real data collected in Dalian and Ningbo (two cities in China). The case study result demonstrates that the establishment of virtual-shopping-experience stores would contribute to reducing the frequency of car trips for offline shopping, as well as the distance of car trips for offline shopping and the time spent in car trips for offline shopping.

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A Fuzzy Bi-level Optimization Method for Urban Ecosystem Management—A Case Study of Xiamen, China

Fang

Wang

Gao

et al. 2023

Environmental Science and Engineering

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Optimization of facility location and size problem based on bi-level multi-objective programming

Cited by 17 publications

References 46 publications

Two‐sided networks coordination for manufacturing technology standards' diffusion from home to host countries: A one‐leader and multiple‐followers Stackelberg game with multiple objectives

Two‐sided networks coordination for manufacturing technology standards' diffusion from home to host countries: A one‐leader and multiple‐followers Stackelberg game with multiple objectives

Optimizing the Location of Virtual-Shopping-Experience Stores Based on the Minimum Impact on Urban Traffic

A Fuzzy Bi-level Optimization Method for Urban Ecosystem Management—A Case Study of Xiamen, China

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