Multi-objective optimization of sustainable biomass supply chain network design

Durmaz Y. G., BİLGEN B.

APPLIED ENERGY, cilt.272, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 272
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1016/j.apenergy.2020.115259
  • Dergi Adı: APPLIED ENERGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Biotechnology Research Abstracts, CAB Abstracts, Communication Abstracts, Compendex, Environment Index, Geobase, INSPEC, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Anahtar Kelimeler: Biomass supply chain network design, Multi-objective optimization, Geographic information systems, Analytical hierarchy process, Mixed integer linear programming, Poultry waste, INTEGRATING GIS, SYSTEM, BIOGAS, MODEL, METHODOLOGY, GENERATION, CHALLENGES, MANAGEMENT, FRAMEWORK, PLANTS
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

This paper addresses the optimal design and planning of the biomass supply chain network that encompasses flow from poultry farms to biogas facilities. A novel multi-stage solution methodology is developed to solve the sustainable biomass supply chain network design problem. Geographical Information Systems, and Analytic Hierarchy Process Techniques are used to determine the candidate location of biogas facilities. The proposed multi-objective mixed integer linear programming model is capable of making strategic decisions (optimal biogas facility locations with capacities) along with the tactical decisions (transportation network flows). The model incorporates the two objective function of maximization of the profit, and minimization of total distance between poultry farms and biogas facilities. The aim is to determine the optimal number, location, and size of the biogas facilities, as well as the network flow, and electricity generated. The applicability of the model and solution methodology is demonstrated through a case study for a poultry supply chain network in Turkey. Additionally, sensitivity analysis is conducted to account for the impact of different parameters on the model. Sensitivity analysis show that both maximum distance parameter, and purchasing prices have major impact on decisions, and financial yield.