Overview of sustainable biomass supply chain: from concept to modelling

Clean Technologies and Environmental Policy

Volumn 18, Issue 7, 2016, Pages 2173-2194

  Hong, Boon Hooi ^a   How, Bing Shen ^a   Lam, Hon Loong ^a  

^a UNIVERSITY OF NOTTINGHAM MALAYSIA CAMPUS   (Malaysia)

Author keywords

Biomass; Biorefinery; Modelling; Optimisation; Supply chain management; Waste to wealth

Indexed keywords

BIOMASS; BIOPRODUCTS; FOSSIL FUELS; MODELS; WASTE MANAGEMENT;

BIOMASS SUPPLY CHAIN; BIOREFINERIES; COMMERCIALISATION; CONVERSION PROCESS; INITIAL POINT; OPTIMISATION METHOD; OPTIMISATIONS; WASTE TO WEALTH;

SUPPLY CHAIN MANAGEMENT;

EID: 84961773017     PISSN: 1618954X     EISSN: 16189558     Source Type: Journal    
DOI: 10.1007/s10098-016-1155-6     Document Type: Article

References (193)

1. Afshar A, Haghani A (2012) Modeling integrated supply chain logistics in real-time large-scale disaster relief operations. Soc-Econ Plan Sci 46:327–338
2. Ahn HJ, Lee H, Park SJ (2003) A flexible agent system for change adaptation in supply chains. Expert Syst Appl 25:603–618
3. Akanle OM, Zhang DZ (2008) Agent-based model for optimising supply-chain configurations. Int J Prod Econ 115:444–460
4. Allen J, Browne M, Hunter A, Boyd J, Palmer H (1998) Logistics management and costs of biomass fuel supply. Int J Phys Distrib Logist Manag 28:463–477
5. Al-Mashari M, Zairi M (2000) Supply-chain re-engineering using enterprise resource planning (ERP) systems: an analysis of a SAP R/3 implementation case. Int J Phys Distrib Logist Manag 30:296–313
6. Altiparmak F, Gen M, Lin L, Karaoglan I (2009) A steady-state genetic algorithm for multi-product supply chain network design. Comput Ind Eng 56:521–537
7. Amaro ACS, Barbosa-Póvoa AP (2004) Optimal supply chain operation—a discrete model formulation. Comput Aided Chem Eng 18:877–882
8. Amaro ACS, Barbosa-Póvoa AP (2005) Optimal scheduling of supply chains: a new continuous-time formulation. Comput Aided Chem Eng 20:1171–1176
9. Amiri A (2006) Designing a distribution network in a supply chain system: formulation and efficient solution procedure. Eur J Oper Res 171:567–576
10. Bandyopadhyay S, Bhattacharya R (2014) Solving a tri-objective supply chain problem with modified NSGA-II algorithm. J Manuf Syst 33:41–50
11. Barany M, Bertok B, Kovacs Z, Friedler F, Fan LT (2011) Solving vehicle assignment problems by process-network synthesis to minimize cost and environmental impact of transportation. Clean Technol Environ Policy 13:637–642
12. Barari S, Agarwal G, Zhang WJ, Mahanty B, Tiwari MK (2012) A decision framework for the analysis of green supply chain contracts: an evolutionary game approach. Expert Syst Appl 39:2965–2976
13. Basoglu N, Daim T, Kerimoglu O (2007) Organizational adoption of enterprise resource planning systems: a conceptual framework. J High Technol Manag Res 18:73–97
14. Beamon BM (1998) Supply chain design and analysis: models and methods. Int J Prod Econ 55:281–294
15. Bertok B, Kalauz K, Sule Z, Friedler F (2013) Combinatorial algorithm for synthesizing redundant structures to increase reliability of supply chains: application to biodiesel supply. Ind Eng Chem Res 52:181–186
16. British Petroleum (BP) (2015a) BP energy outlook 2035. www.bp.com/energyoutlook. Accessed 26 June 2015
17. British Petroleum (BP) (2015b) BP Statistical review of world energy. www.bp.com/statisticalreview. Accessed 26 June 2015
18. Brooks S, Wang X, Sarker S (2012) Unpacking Green IS: a review of the existing literature and directions for the future. In: Vom Brocke J, Seidel S, Recker J (eds) Green business process management. Springer-Verlag, Berlin, pp 15–37
19. Bullnheimer B, Hartl RF, Strauss C (1999) An improved Ant System algorithm for the Vehicle Routing Problem. Ann Oper Res 89:319–328
20. Cachon G, Netessine S (2004) Game theory in supply chain analysis. In: Simchi-Levi D, Wu SD, Shen ZJ (eds) Handbook of quantitative supply chain analysis: modeling in the eBusiness era. Kluwer, Boston
21. Cakravastia A, Toha IS, Nakamura N (2002) A two-stage model for the design of supply chain networks. Int J Prod Econ 80:231–248
22. Cambero C, Sowlati T (2014) Assessment and optimization of forest biomass supply chains from economic, social and environmental perspectives—a review of literature. Renew Sustain Energy Rev 36:62–73
23. Cambero C, Sowlate T, Pavel M (2015) Economic and life cycle environmental optimisation of forest-based biorefinery supply chains for bioenergy and biofuel production. Chem Eng Res Des. doi:10.1016/j.cherd.2015.10.040
24. Carvalho A, Matos HA, Gani R (2013) SustainPro—A tool for systematic process analysis, generation and evaluation of sustainable design alternatives. Comput Chem Eng 50:8–27
25. Chang YH (2010) Adopting co-evolution and constraint-satisfaction concept on genetic algorithms to solve supply chain network design problems. Expert Syst Appl 37:6919–6930
26. Che ZH, Chiang CJ (2010) A modified Pareto genetic algorithm for multi-objective build-to-order supply chain planning with product assembly. Adv Eng Softw 41:1011–1022
27. Chen TG, Ju CH (2013) A novel artificial bee colony algorithm for solving the supply chain network design under disruption scenarios. Int J Comput Appl Technol 47:289–296
28. Chen CL, Lee WC (2004) Multi-objective optimization of multi-echelon supply chain networks with uncertain product demands and prices. Comput Chem Eng 28:1131–1144
29. Chen YJ, Sheu JB (2009) Environmental-regulation pricing strategies for green supply chain management. Transp Res Part E 45:667–677
30. Cheng BY, Leung JYT, Li K (2015) Integrated scheduling of production and distribution to minimize total cost using an improved ant colony optimization method. Comput Ind Eng 83:217–225
31. Chofreh AG, Goni FA, Shaharoun AM, Ismail S, Klemeš JJ (2014) Sustainable enterprise resource planning: imperatives and research directions. J Clean Prod 71:139–147
32. Chong FK, Lawrence KK, Lim PP, Poon MCY, Foo DCY, Lam HL, Tan RR (2014) Planning of carbon capture storage deployment using process graph approach. Energy 76:641–651
33. Christopher M (2000) The agile supply chain: competing in volatile markets. Ind Mark Manag 29:37–44
34. Christopher M, Peck H (2004) Building the resilient supply chain. Int J Logist Manag 15:1–14
35. Christopher M, Lowson R, Peck H (2004) Creating agile supply chains in the fashion industry. Int J Retail Distrib Manag 32:367–376
36. Čuček L, Martín M, Grossmann IE, Kravanja Z (2014) Multi-period synthesis of optimally integrated biomass and bioenergy supply network. Comput Chem Eng 66:57–70
37. Cundiff JS, Dias N, Sherali HD (1997) A linear programming approach for designing a herbaceous biomass delivery system. Bioresour Technol 59:47–55
38. Dogan K, Goetschalckx M (1999) A primal decomposition method for the integrated design of multi-period production-distribution systems. IIE Trans 31:1027–1036
39. Erol I, Ferrell WG Jr (2004) A methodology to support decision making across the supply chain of an industrial distributor. Int J Prod Econ 89:119–129
40. Esmaeili M, Aryanezhad MB, Zeephongsekul P (2009) A game theory approach in seller–buyer supply chain. Eur J Oper Res 195:442–448
41. Fan LT, Kim Y, Yun C, Park SB, Park S, Bertok B, Friedler F (2009) Design of optimal and near-optimal enterprise-wide supply networks for multiple products in the process industry. Ind Eng Chem Res 48:2003–2008
42. Fan LT, Lin YC, Shafie S, Bertok B, Friedler F (2012) Exhaustive identification of feasible pathways of the reaction catalyzed by a catalyst with multiactive sites via a highly effective graph-theoretic algorithm: application to ethylene hydrogenation. Ind Eng Chem Res 51:2548–2552
43. Feng G, Fan LT, Seib PA, Bertok B, Kalotai L, Friedler F (2003) Graph-theoretic method for the algorithmic synthesis of azeotropic-distillation systems. Ind Eng Chem Res 42:3602–3611
44. Fernando S, Adhikari S, Chandrapal C, Murali N (2006) Biorefineries: current status, challenges, and future direction. Energy Fuels 20:1727–1737
45. Fiedler P, Lange M, Schultze M (2007) Supply logistics for the industrialized use of biomass principles and planning approach. In:International symposium on logistics and industrial informatics, pp 41–46
46. Fiksel J (2006) Sustainability and resilience: toward a systems approach. Sustainability 2:14–21
47. Finnveden G, Moberg Å (2005) Environmental systems analysis tools—an overview. J Clean Prod 13:1165–1173
48. Fischer T, Gehring H (2005) Planning vehicle transhipment in a seaport automobile terminal using a multi-agent system. Eur J Oper Res 166:726–740
49. Forget P, D’Amours S, Frayret JM (2008) Multi-behavior agent model for planning in supply chains: an application to the lumber industry. Robot Comput-Integr Manuf 24:664–679
50. Fox M, Barbuceanu M, Teigen R (2000) Agent-oriented supply-chain management. Int J Flex Manuf Syst 12:165–188
51. Franca RB, Jones EC, Richards CN, Carlson JP (2010) Multi-objective stochastic supply chain modeling to evaluate tradeoffs between profit and quality. Int J Prod Econ 127:292–299
52. Friedler F, Tarjan K, Huang YW, Fan LT (1992) Combinatorial algorithms for process synthesis. Comput Chem Eng 16:313–320
53. Fu J, Fu Y (2015) An adaptive multi-agent system for cost collaborative management in supply chains. Eng Appl Artif Intell 44:91–100
54. García-Ojeda JC, Bertok B, Friedler F, Fan LT (2013) Building-evacuation-route planning via time-expanded process-network synthesis. Fire Saf J 61:338–347
55. Gen M, Syarif A (2005) Hybrid genetic algorithm for multi-time period production/distribution planning. Comput Ind Eng 48:799–809
56. Ghasimi SA, Ramli R, Saibani N (2014) A genetic algorithm for optimizing defective goods supply chain costs using JIT logistics and each-cycle lengths. Appl Math Model 38:1534–1547
57. Giannakis M, Louis M (2011) A multi-agent based framework for supply chain risk management. J Purch Supply Manag 17:23–31
58. Gold S, Seuring S (2011) Supply chain and logistics issues of bio-energy production. J Clean Prod 19:32–42
59. Goni FA, Chofreh AG, Sahran S (2011) Critical success factors for enterprise resource planning system implementation: a case study in Malaysian SME. Int J Adv Sci Eng Inf Technol 1:200–205
60. Graves SC, Willems SP (2005) Optimizing the supply chain configuration for new products. Manag Sci 51:1165–1180
61. Guest G, Bright RM, Cherubini F, Michelsen O, Strømman AH (2011) Life cycle assessment of biomass-based combined heat and power plants. J Ind Ecol 15:908–921
62. Guillén G, Mele FD, Bagajewicz MJ, Espuña A, Puigjaner L (2005a) Multiobjective supply chain design under uncertainty. Chem Eng Sci 60:1535–1553
63. Guillén G, Mele FD, Urbano F, Espuña A, Puigjaner L (2005b) An agent-based approach for supply chain retrofitting under uncertainty. Comput Chem Eng 31:722–735
64. Gungor A, Gupta SM (1999) Issues in environmentally conscious manufacturing and product recovery: a survey. Comput Ind Eng 36:811–853
65. Guo R, Tang Q (2009) An optimized supply chain planning model for manufacture company based on JIT. Int J Bus Manag 3:129–133
66. Hanafizadeh P, Sherkat MH (2009) Designing fuzzy-genetic learner model based on multi-agent systems in supply chain management. Expert Syst Appl 36:10120–10134
67. Harland CM (1996) Supply chain management: relationships, chains and networks. Br J Manag 7:63–80
68. Hertz DB, Thomas H (1985) Risk analysis and its applications. Strateg Manag J 6:295
69. Hong BH, Lam HL (2015) Novel approach for integrated biomass supply chain. Chem Eng Trans 45:475–480
70. Hoogwijk M, Faaij A, van den Broek R, Berndes G, Gielen D, Turkenburg W (2003) Exploration of the ranges of the global potential of biomass for energy. Biomass Bioenergy 25:119–133
71. How BS, Hong BH, Lam HL, Friedler F (2015) Synthesis of multiple biomass corridor via decomposition approach: a P-graph application. J Clean Prod. doi:10.1016/j.jclepro.2015.12
72. Huang GQ, Zhang XY, Lo VH (2007) Integrated configuration of platform products and supply chains for mass customization: a game-theoretic approach. IEEE Trans Eng Manage 54:156–171
73. Huang Y, Huang GQ, Newman ST (2011) Coordinating pricing and inventory decisions in a multi-level supply chain: a game-theoretic approach. Transp Res Part E 47:115–129
74. Huisman W, Venturi P, Molenaar J (1997) Costs of supply chains of Miscanthus giganteus. Ind Crops Prod 6:353–366
75. Iakovou E, Karagiannidis A, Vlachos D, Toka A, Malamakis A (2010) Waste biomass-to-energy supply chain management: a critical synthesis. Waste Manag 30:1860–1870
76. International Energy Agency (IEA) (2015) Key World Energy Statistics 2015. www.iea.org/publications/freepublications/publication/key-world-energy-statistics-2015.html. Accessed 10 Oct 2015
77. Jayaraman V, Pirkul H (2001) Planning and coordination of production and distribution facilities for multiple commodities. Eur J Oper Res 133:394–408
78. Jayaraman V, Ross A (2003) A simulated annealing methodology to distribution network design and management. Eur J Oper Res 144:629–645
79. Kaihara T (2003) Multi-agent based supply chain modelling with dynamic environment. Int J Prod Econ 85:263–269
80. Kalauz K, Süle Z, Bertok B, Fan LT (2012) Extending process-network synthesis algorithms with time bounds for supply network design. Chem Eng Trans 29:259–264
81. Kandananond K (2014) A roadmap to green supply chain system through enterprise resource planning (ERP) implementation. Proc Eng 69:377–382
82. Kannan G, Sasikumar P, Devika K (2010) A genetic algorithm approach for solving a closed loop supply chain model: a case of battery recycling. Appl Math Model 34:655–670
83. Kasivisvanathan H, Tan RR, Ng DKS, Abdul Aziz MK, Foo DCY (2014) Heuristic framework for the debottlenecking of a palm oil-based integrated biorefinery. Chem Eng Res Des 92:2071–2082
84. Kelle P, Akbulut A (2005) The role of ERP tools in supply chain information sharing, cooperation, and cost optimization. Int J Prod Econ 93–94:41–52
85. Klemeš JJ, Lam HL (2009) Heat integration, energy efficiency, saving and security. Energy 34:1669–1673
86. Klemeš JJ, Varbanov PS, Wang Q, Lund H (2013) Process integration, modelling and optimisation for energy saving and pollution reduction. Energy 55:1–4
87. Koc E (2010) Bees Algorithm: theory, improvements and applications. Ph.D. thesis, Cardiff University, United Kingdom
88. Koh SCL, Saad SM (2006) Managing uncertainty in ERP-controlled manufacturing environments in SMEs. Int J Prod Econ 101:109–127
89. Kostin A, Mele F, Guillén-Gozálbez G (2011) Multi-objective optimization of integrated bioethanol-sugar supply chains considering different LCA metrics simultaneously. Comput Aided Chem Eng 29:1276–1280
90. Kudakasseril Kurian J, Raveendran Nair G, Hussain A, Vijaya Raghavan GS (2013) Feedstocks, logistics and pre-treatment processes for sustainable lignocellulosic biorefineries: a comprehensive review. Renew Sustain Energy Rev 25:205–219
91. Kuhn JR, Sutton SG (2010) Continuous auditing in ERP system environments: the current state and future directions. J Inf Syst 24:91–112
92. Laínez JM, Bojarski A, Espuña A, Puigjaner L (2008) Mapping environmental issues within supply chains: a LCA based approach. Comput Aided Chem Eng 25:1131–1136
93. Lam HL (2013) Extended P-graph applications in supply chain and Process Network Synthesis. Curr Opin Chem Eng 2:475–486
94. Lam HL, Varbanov PS, Klemeš JJ (2010a) Minimising carbon footprint of regional biomass supply chains. Resour Conserv Recycl 54:303–309
95. Lam HL, Varbanov PS, Klemeš JJ (2010b) Optimisation of regional energy supply chains utilising renewables: P-graph approach. Comput Chem Eng 34:782–792
96. Lam HL, Ng WPQ, Ng RT, Ng EH, Aziz MKA, Ng DKS (2013) Green strategy for sustainable waste-to-energy supply chain. Energy 57:4–16
97. Lam HL, How BS, Hong BH (2015) Green supply chain towards sustainable industry development. In: Klemeš JJ (ed) Assessing and measuring environmental impact and sustainability. Butterworth-Heinemann, Oxford, pp 409–449
98. Lamming R, Program IMV (1989) The causes and effects of structural changes in the European automotive components industry: a report. Center for Technology, Policy and Industrial Development, Massachusetts Institute of Technology, Cambridge
99. Law CCH, Chen CC, Wu BJP (2010) Managing the full ERP life-cycle: considerations of maintenance and support requirements and IT governance practice as integral elements of the formula for successful ERP adoption. Comput Ind 61:297–308
100. Lee YH, Kim SH (2000) Optimal production-distribution planning in supply chain management using a hybrid simulation-analytic approach. In: Proceedings of the 2000 winter simulation conference, vol 1–2, pp 1252–1259
101. Lee J, Siau K, Hong S (2003) Enterprise integration with ERP and EAI. Commun ACM 46:54–60
102. Li D, O’Brien C (1999) Integrated decision modelling of supply chain efficiency. Int J Prod Econ 59:147–157
103. Li H, Womer K (2012) Optimizing the supply chain configuration for make-to-order manufacturing. Eur J Oper Res 221:118–128
104. Liang TF (2006) Distribution planning decisions using interactive fuzzy multi-objective linear programming. Fuzzy Sets Syst 157:1303–1316
105. Liang TF (2008) Fuzzy multi-objective production/distribution planning decisions with multi-product and multi-time period in a supply chain. Comput Ind Eng 55:676–694
106. Liang WY, Huang CC (2006) Agent-based demand forecast in multi-echelon supply chain. Decis Support Syst 42:390–407
107. Lim CH, Lam HL (2016) Biomass supply chain optimisation via novel Biomass Element Life Cycle Analysis (BELCA). Appl Energy 161:733–745
108. Lim MK, Zhang Z, Goh W (2009) An iterative agent bidding mechanism for responsive manufacturing. Eng Appl Artif Intell 22:1068–1079
109. Lin FR, Lin YY (2006) Integrating multi-agent negotiation to resolve constraints in fulfilling supply chain orders. Electron Commer Res Appl 5:313–322
110. Lin FR, Kuo HC, Lin SM (2008) The enhancement of solving the distributed constraint satisfaction problem for cooperative supply chains using multi-agent systems. Decis Support Syst 45:795–810
111. Linthicum DS (1999) Enterprise application integration. Addison-Wesley Professional, Boston
112. Liu Z, Huang Y (2015) Sustainability enhancement under uncertainty: a Monte Carlo-based simulation and system optimization method. Clean Technol Environ Policy 17:1757–1768
113. Lopez C, Salmeron JL (2014) Dynamic risks modelling in ERP maintenance projects with FCM. Inf Sci 256:25–45
114. Lummus RR, Vokurka RJ (1999) Defining supply chain management: a historical perspective and practical guidelines. Ind Manag Data Syst 99:11–17
115. Marinos T, Zahir I (2003) Integrating cross-enterprise systems: an innovative framework for the introduction of enterprise application integration. In: Proceedings of the 11th European conference on information systems 1972–1988
116. Mastrocinque E, Yuce B, Lambiase A, Packianather MS (2013) A multi-objective optimisation for supply chain network using the bees algorithm. Int J Eng Bus Manag 5:1–11
117. Min H, Zhou G (2002) Supply chain modeling: past, present and future. Comput Ind Eng 43:231–249
118. Moncayo-Martínez LA, Recio G (2014) Bi-criterion optimisation for configuring an assembly supply chain using Pareto ant colony meta-heuristic. J Manuf Syst 33:188–195
119. Moncayo-Martínez LA, Zhang DZ (2011) Multi-objective ant colony optimisation: a meta-heuristic approach to supply chain design. Int J Prod Econ 131:407–420
120. Moncayo-Martínez LA, Zhang DZ (2013) Optimising safety stock placement and lead time in an assembly supply chain using bi-objective MAX–MIN ant system. Int J Prod Econ 145:18–28
121. More D, Babu AS (2008) Perspectives, practices and future of supply chain flexibility. Int J Bus Excell 1:302–336
122. Murphy F, Devlin G, McDonnell K (2014) Forest biomass supply chains in Ireland: a life cycle assessment of GHG emissions and primary energy balances. Appl Energy 116:1–8
123. Nagarajan M, Sošić G (2008) Game-theoretic analysis of cooperation among supply chain agents: review and extensions. Eur J Oper Res 187:719–745
124. Nagurney A, Yu M (2012) Sustainable fashion supply chain management under oligopolistic competition and brand differentiation. Int J Prod Econ 135:532–540
125. Nelson D, Marsillac E, Rao S (2012) Antecedents and evolution of the green supply chain. J Oper Supply Chain Manag 1:29–43
126. Ness B, Urbel-Piirsalu E, Anderberg S, Olsson L (2007) Categorising tools for sustainability assessment. Ecol Econ 60:498–508
127. Ng WPQ, Lam HL (2014) A supply network optimisation with functional clustering of industrial resources. J Clean Prod 71:87–97
128. Ng WPQ, Lam HL, Yusup S (2013) Supply network synthesis on rubber seed oil utilisation as potential biofuel feedstock. Energy 55:82–88
129. Ng WPQ, Promentilla MA, Lam HL (2015) An algebraic approach for supply network synthesis. J Clean Prod 88:326–335
130. Nwe ES, Adhitya A, Halim I, Srinivasan R (2010) Green supply chain design and operation by integrating LCA and dynamic simulation. Comput Aided Chem Eng 28:109–114
131. Oliver RK, Webber MD (1982) Supply-chain management: logistics catches up with strategy. In: Christopher M (ed) Logistics: the strategic issues. Chapman & Hall, London, pp 192–209
132. Paksoy T, Pehlivan NY, Özceylan E (2012) Application of fuzzy optimization to a supply chain network design: a case study of an edible vegetable oils manufacturer. Appl Math Model 36:2762–2776
133. Pal K, Karakostas B (2014) A multi agent-based service framework for supply chain management. Proc Comput Sci 32:53–60
134. Pasandideh SHR, Niaki STA, Asadi K (2015) Bi-objective optimization of a multi-product multi-period three-echelon supply chain problem under uncertain environments: nSGA-II and NRGA. Inf Sci 292:57–74
135. Paulo H, Azcue X, Barbosa-Póvoa AP, Relvas S (2015) Supply chain optimization of residual forestry biomass for bioenergy production: the case study of Portugal. Biomass Bioenergy 83:245–256
136. Peidro D, Mula J, Poler R, Verdegay JL (2009) Fuzzy optimization for supply chain planning under supply, demand and process uncertainties. Fuzzy Sets Syst 160:2640–2657
137. Petrovic D, Roy R, Petrovic R (1998) Modelling and simulation of a supply chain in an uncertain environment. Eur J Oper Res 109:299–309
138. Pham DT, Ghanbarzadeh A, Koc E, Otri S, Rahim S, Zaidi M (2005) The Bees Algorithm: A novel too for complex optimisation problems. In: Proceedings of the 2nd international virtual conference on intelligent production machines and systems, pp 454–459
139. Power D (2005) Supply chain management integration and implementation: a literature review. Supply Chain Manag 10(4):10252–10263
140. Pucker J, Zwart R, Jungmeier G (2012) Greenhouse gas and energy analysis of substitute natural gas from biomass for space heat. Biomass Bioenergy 38:95–101
141. Ramezani M, Bashiri M, Tavakkoli-Moghaddam R (2013) A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level. Appl Math Model 37:328–344
142. Ren J, Dong L, Sun L, Goodsite ME, Tan S, Dong L (2015) Life cycle cost optimisation of biofuel supply chains under uncertainties based on interval linear programming. Bioresour Technol 187:6–13
143. Robinson EP, Satterfield RK (1998) Designing distribution systems to support vendor strategies in supply chain management. Decis Sci 29:685–706
144. Ryu J (2005) A multi-level programming optimization approach to enterprise-wide supply chain planning. Comput Aided Chem Eng 20:571–576
145. Sadhukhan J, Ng KS, Hernandez EM (2014) Biorefineries and chemical processes: design, integration and sustainability analysis. Wiley, New York
146. Seifert RW, Zequeira RI, Liao S (2012) A three-echelon supply chain with price-only contracts and sub-supply chain coordination. Int J Prod Econ 138:345–353
147. Sharma B, Ingalls RG, Jones CL, Khanchi A (2013) Biomass supply chain design and analysis: basis, overview, modeling, challenges, and future. Renew Sustain Energy Rev 24:608–627
148. Sheu JB (2011) Bargaining framework for competitive green supply chains under governmental financial intervention. Transp Res Part E 47:573–592
149. Silva CA, Sousa J, Runkler T, Sá da Costa J (2004) A multi-agent approach for supply chain management using ant colony optimization. Proc IEEE Int Conf Syst Man Cybern 2:1938–1943
150. Silva CA, Sousa J, Runkler T, Sá da Costa J (2009) Distributed supply chain management using ant colony optimization. Eur J Oper Res 199:349–358
151. Simchi-Levi D, Kaminsky P, Simchi-Levi E (2013) Designing and managing the supply chain. McGraw-Hill Higher Education, New York
152. Sitek P, Nielsen IE, Wikarek J (2014) A hybrid multi-agent approach to the solving supply chain problems. Proc Comput Sci 35:1557–1566
153. Slack N (1991) The manufacturing advantage: achieving competitive manufacturing operations. Mercury Business Books, New York
154. Sobel MJ, Turcic D (2008) Risk aversion and supply chain contract negotiation. Working paper, Case Western Reserve University, Cleveland
155. Srivastava SK (2007) Green supply-chain management: a state-of-the-art literature review. Int J Manag Rev 9:53–80
156. Starr R, Newfrock J, Delurey M (2003) Enterprise Resilience: managing Risk in the Networked Economy. Int J Prod Res 30:1–10
157. Stevens GC (1989) Integrating the supply chain. Int J Phys Distrib Mater Manag 19:3–8
158. Sukumara S, Amundson J, Badurdeen F, Seay J (2015) A comprehensive techno-economic analysis tool to validate long-term viability of emerging biorefining processes. Clean Technol Environ Policy 17:1793–1806
159. Süle Z, Bertok B, Friedler F, Fan LT (2011) Optimal design of supply chains by P-graph framework under uncertainties. Chem Eng Trans 25:453–458
160. Swaminathan JM, Smith SF, Sadeh NM (1998) Modeling supply chain dynamics: a multiagent approach. Decis Sci 29:607–632
161. Syam SS (2002) A model and methodologies for the location problem with logistical components. Comput Oper Res 29:1173–1193
162. Syarif A, Yun Y, Gen M (2002) Study on multi-stage logistic chain network: a spanning tree-based genetic algorithm approach. Comput Ind Eng 43:299–314
163. Tang JP, Lam HL, Aziz MKA, Morad NA (2015) Game theory approach in Malaysia palm biomass industry analysis. Chem Eng Trans 45:463–468
164. Teimoury E, Haddad H (2013) A bee algorithm for parallel batch production scheduling. Int J 2:169–171
165. Themistocleous M, Irani Z, O’Keefe RM (2001) ERP and application integration: exploratory survey. Bus Process Manag J 7:195–204
166. Truong TH, Azadivar F (2005) Optimal design methodologies for configuration of supply chains. Int J Prod Res 43:2217–2236
167. Turan P, Yapici PN, Eren Ö (2012) Application of fuzzy optimization to a supply chain network design: a case study of an edible vegetable oils manufacturer. Appl Math Model 36:2762–2776
168. Vance L, Cabezas H, Heckl I, Bertok B, Friedler F (2013) Synthesis of sustainable energy supply chain by the P-graph framework. Ind Eng Chem Res 52:266–274
169. Von Neumann J, Morgenstern O (1947) Theory of games and economic behavior. Princeton University Press, Princeton
170. Vonderembse MA, Uppal M, Huang SH, Dismukes JP (2006) Designing supply chains: towards theory development. Int J Prod Econ 100:223–238
171. Wan YK, Ng RTL, Ng DKS, Aviso KB, Tan RR (2015) Fuzzy multi-footprint optimisation (FMFO) for synthesis of a sustainable value chain: malaysian sago industry. J Clean Prod. doi:10.1016/j.jclepro.2015.05.050
172. Wang HS (2009) A two-phase ant colony algorithm for multi-echelon defective supply chain network design. Eur J Oper Res 192:243–252
173. Wang KJ, Chen MJ (2009) Cooperative capacity planning and resource allocation by mutual outsourcing using ant algorithm in a decentralized supply chain. Expert Syst Appl 36:2831–2842
174. Wang KJ, Lee CH (2015) A revised ant algorithm for solving location–allocation problem with risky demand in a multi-echelon supply chain network. Appl Soft Comput 32:311–321
175. Womack JP, Jones DT, Roos D (2007) The machine that changed the world: the story of lean production—Toyota’s secret weapon in the global car wars that is now revolutionizing world industry. Free Press, New York
176. Wood A (1997) Extending the supply chain: strengthening links with IT. Chem Week 159:26
177. Xu R, Zhai X (2010) Analysis of supply chain coordination under fuzzy demand in a two-stage supply chain. Appl Math Model 34:129–139
178. Yan H, Yu Z, Edwin Cheng TC (2003) A strategic model for supply chain design with logical constraints: formulation and solution. Comput Oper Res 30:2135–2155
179. Yeh WC, Chuang MC (2011) Using multi-objective genetic algorithm for partner selection in green supply chain problems. Expert Syst Appl 38:4244–4253
180. Yılmaz S, Selim H (2013) A review on the methods for biomass to energy conversion systems design. Renew Sustain Energy Rev 25:420–430
181. Yuce B, Mastrocinque E, Lambiase A, Packianather MS, Pham DT (2014) A multi-objective supply chain optimisation using enhanced Bees Algorithm with adaptive neighbourhood search and site abandonment strategy. Swarm Evol Comput 18:71–82
182. Yun Y, Moon C, Kim D (2009) Hybrid genetic algorithm with adaptive local search scheme for solving multistage-based supply chain problems. Comput Ind Eng 56:821–838
183. Zamarripa M, Silvente J, Espuña A (2012) Supply chain planning under uncertainty using genetic algorithms. Comput Aided Chem Eng 30:1306–1314
184. Zamarripa MA, Aguirre AM, Méndez CA, Espuña A (2013) Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments. Chem Eng Res Des 91:1588–1600
185. Zegordi SH, Abadi INK, Nia MAB (2010) A novel genetic algorithm for solving production and transportation scheduling in a two-stage supply chain. Comput Ind Eng 58:373–381
186. Zhang T, Zhang D (2007) Agent-based simulation of consumer purchase decision-making and the decoy effect. J Bus Res 60:912–922
187. Zhang DZ, Anosike AI, Lim MK, Akanle OM (2006) An agent-based approach for e-manufacturing and supply chain integration. Comput Ind Eng 51:343–360
188. Zhang S, Lee CKM, Choy KL, Ho W, Ip WH (2014) Design and development of a hybrid artificial bee colony algorithm for the environmental vehicle routing problem. Transp Res Part D 31:85–99
189. Zhang LL, Lee C, Zhang S (2016) An integrated model for strategic supply chain design: formulation and ABC-based solution approach. Expert Syst Appl 52:39–49
190. Zhao Y, Wang S, Cheng TCE, Yang X, Huang Z (2010) Coordination of supply chains by option contracts: a cooperative game theory approach. Eur J Oper Res 207:668–675
191. Zhao R, Neighbour G, Han J, McGuire M, Deutz P (2012) Using game theory to describe strategy selection for environmental risk and carbon emissions reduction in the green supply chain. J Loss Prev Process Ind 25:927–936
192. Zhu QH, Dou YJ (2007) Evolutionary game model between governments and core enterprises in greening supply chains. Syste Eng 27:85–89
193. Zolfpour-Arokhlo M, Selamat A, Hashim SZM (2013) Route planning model of multi-agent system for a supply chain management. Expert Syst Appl 40:1505–1518