Biologically inspired optimization of construction sector eco industrial park networks using food web metrics
摘要
Industrial symbiosis (IS) and eco-industrial parks (EIPs) are increasingly promoted as practical pathways to circular economy transitions in resource-intensive sectors such as construction, where diverse waste streams, quality variability, and fragmented supply chains often constrain the number and stability of feasible exchanges. Building on biomimetic design principles, this study investigates whether construction-sector EIP networks can be optimized to better resemble selected structural patterns observed in biological food webs, and how optimization choices and participation rules influence the resulting network topology. Using a construction symbiosis database and five theoretical exchange scenarios, scenario-constrained optimization models are formulated to seek proximity to detritus-inclusive biological food-web reference values. Four objective function types (OFTs), representing alternative ways of aggregating multi-metric deviation from benchmarks, were tested in two parallel model families: one excluding connectance from the objective set and one explicitly targeting connectance to assess its conditioning role. A genetic algorithm was used to optimize the scenario-constrained network models and efficiently explore the large combinatorial solution space. Results show that structural proximity to the selected food-web benchmarks is configuration-dependent. Scenario rules and OFT choice systematically steer solutions toward distinct network morphologies, producing clear trade-offs across metrics rather than uniform improvement. Across best-performing configurations, the ratio of waste-providing to waste-receiving firms was comparatively close to benchmark levels in some cases but showed notable deviations in others, while link density and cyclicity exhibited persistent deficits, indicating that achieving dense, highly cycling structures is challenging under construction-specific feasibility constraints. Explicitly including connectance reduced the tendency of some OFTs to converge to extreme connectivity regimes and yielded more balanced metric profiles, highlighting connectance as a structuring constraint that limits extreme connectivity rather than as evidence of ecological realism. Reciprocity-oriented participation rules, particularly those requiring receiver firms to also provide exchanges, were associated with more benchmark-consistent solutions under certain OFT and connectance-included combinations, rather than uniformly dominating across all cases. For practice, the findings suggest that structurally informed bio-inspired EIP planning may benefit from treating connectance as a controlled design parameter and considering reciprocal participation policies where they are compatible with the selected objective formulation and feasibility constraints. Future research should integrate exchange quantities, cost and quality constraints, and uncertainty dynamics, and should report Pareto-efficient solution sets to support stakeholder selection and implementation.