Personalized service product family design optimization considering crowdsourced service operations

Zhou, Kaihong; Du, Gang; Jiao, Roger J.

doi:10.1016/j.cie.2022.107973

Cited by 15 publications

(2 citation statements)

References 46 publications

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“…Bilevel programming involves two decision-makers and is well-suited for addressing leader-follower optimization decision-making problems [38]. It has garnered significant attention in academia and has been applied across various fields, including reconfigurable process planning [39], crowdsourcing service operations, product family design of personalized services [40], and the data-driven newsvendor problem [41]. Unlike ordinary mathematical programming, bilevel programming presents unique challenges.…”

Section: Bilevel Programmingmentioning

confidence: 99%

Optimal Sustainable Manufacturing for Product Family Architecture in Intelligent Manufacturing: A Hierarchical Joint Optimization Approach

Ma,

Chen,

2024

Sustainability

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As consumers and governments prioritize cost-effectiveness and ecological sustainability, the limitations of traditional manufacturing paradigms become apparent in the context of constrained resources. The adverse effects of these paradigms on the environment and society hinder the achievement of a sustainable product life cycle. Intelligent manufacturing processes offer a solution by efficiently gathering meaningful data, such as usage and product recycling information, from previous product generations to enhance product design and subsequent sustainable manufacturing processes (SMPs). Modular product family architecture (PFA) design holds promise in promoting product sustainability and addressing diverse consumer needs. PFA design and SMPs are inherently interconnected within intelligent manufacturing frameworks. This paper aims to integrate the decision-making processes underlying PFA with SMPs. We model integrated PFA and SMP decisions as a Stackelberg game, which involves hierarchical joint optimization (HJO) for assessing product modularity and sustainable manufacturing fulfillment. We develop a bilevel 0–1 integer nonlinear programming model to represent the HJO decision-making process and propose a nested genetic algorithm (NGA) to solve the HJO problem. A case study with a laptop is conducted to validate the feasibility and potential of the proposed HJO model for joint optimization problems in PFA design and SMPs.

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Section: Bilevel Programmingmentioning

confidence: 99%

Optimal Sustainable Manufacturing for Product Family Architecture in Intelligent Manufacturing: A Hierarchical Joint Optimization Approach

Ma,

Chen,

2024

Sustainability

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“…The future manufacturing paradigm for delivery of MaaS, i.e., crowdsourced manufacturing, has been discussed [21,30]. In crowdsourced manufacturing, enterprises can share manufacturing resources according to their needs and capabilities [31], and the supply of raw materials, assembly, manufacturing, transportation, etc., of products can be realized by manufacturing service providers through a cyber platform in a crowdsourcing model [32,33]. Existing studies on product design in crowdsourced manufacturing include product family design considering postponement contracting decisions [32] and service product family design [33].…”

Section: Future Manufacturing Trends Towards Maasmentioning

confidence: 99%

Low-Carbon Product Family Planning for Manufacturing as a Service (MaaS): Bilevel Optimization with Linear Physical Programming

2022

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The conversion of manufacturing functional areas towards services implies a paradigm of Manufacturing as a Service (MaaS). It transforms the product fulfillment process to a distributed one via a service-oriented manufacturing platform. Successful MaaS operational planning must be coordinated with low-carbon product family planning (PFP) at the front end of product design and development. These changes challenge the traditional PFP design, considering its manufacturer loading balancing (MLB) problem, which is limited to integrated product fulfillment. This paper proposes a leader–follower interactive decision-making mechanism for distributed collaborative product fulfillment of low-carbon PFP and MLB based on a Stackelberg game. A bilevel optimization model with linear physical programming was developed and solved, comprising an upper-level PFP optimization problem and a lower-level MLB optimization problem. The upper-level PFP aims to determine the optimal configuration of each product variant with the objective of maximizing the market share and the total profit in the product family. The lower-level MLB seeks for the optimal partition of manufacturing processes among manufacturers in order to minimize the low-carbon operation cost of product variants and balance the loads among manufacturers. A case study of WS custom kitchen product family design for MaaS is reported to demonstrate the feasibility and potential of the proposed bilevel interactive optimization approach.

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A decision framework for incorporating the coordination and behavioural issues in sustainable supply chains in digital economy

et al. 2022

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Personalized service product family design optimization considering crowdsourced service operations

Cited by 15 publications

References 46 publications

Optimal Sustainable Manufacturing for Product Family Architecture in Intelligent Manufacturing: A Hierarchical Joint Optimization Approach

Optimal Sustainable Manufacturing for Product Family Architecture in Intelligent Manufacturing: A Hierarchical Joint Optimization Approach

Low-Carbon Product Family Planning for Manufacturing as a Service (MaaS): Bilevel Optimization with Linear Physical Programming

A decision framework for incorporating the coordination and behavioural issues in sustainable supply chains in digital economy

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