Task derivation and decomposition in crowdsourced manufacturing by bilevel coordinated optimization of product family planning and manufacturer load balancing

Abstract

Crowdsourcing in manufacturing enables collaborative product fulfillment through supply contracting, aligned with task derivation and decomposition. Effective coordination of product family planning (PFP) with manufacturing processes is crucial for manufacturer load balancing (MLB). This paper focuses on game-theoretic decisions in crowdsourcing task derivation and decomposition, proposing a bilevel coordinated optimization model formulated as a Stackelberg game. PFP decisions are treated as profit maximization at the upper level, while MLB decisions are formulated as cost minimization at the lower level. A nested-bilevel genetic algorithm is developed for efficient model solution. A case study of tank trailer crowdsourced manufacturing demonstrates the benefits of employing the bilevel game-theoretic decision model, achieving optimal task derivation and decomposition and coordinated solutions for both the platform and crowdsourced manufacturers.