To improve the biogas energy development structure, this paper studies the multi objective dynamic programming in its investment system. Limited resource has bandaged the ideal of investors. Variety of stages in the systems and in object function us state diversion, stage decision and overall decision constitute optimization problem. This paper applied multi-objects fuzzy optimization dynamic-state scheme model to establish the math-model of having disagreement of amount, and the resource allocation problem not only having quantum object but also having qualitative object. The decision makers need to make a decision assigning the different area condition and resource to invest different scales of biogas projects under exploring constraint. Due to the lack of historical data, some coefficients are considered as fuzzy numbers according to experts advices. Therefore, a multi-objective dynamic optimization model with possibilities constraints under the fuzzy environment is developed to control the pollution and realize the economic growth. Finally, a practical case is proposed to show the efficiency of the proposed model and algorithm. A bi-level biogas investment planning multiple objective multistage programming model is constructed.
[1]
Massimo Paolucci,et al.
A new discrete particle swarm optimization approach for the single-machine total weighted tardiness scheduling problem with sequence-dependent setup times
,
2009,
Eur. J. Oper. Res..
[2]
Jiuping Xu,et al.
Applying Optimal Control Model to Dynamic Equipment Allocation Problem: Case Study of Concrete-Faced Rockfill Dam Construction Project
,
2011
.
[3]
Michele Pinelli,et al.
Analysis of biogas compression system dynamics
,
2009
.
[4]
Ji Zhao,et al.
Comprehensive utilizations of biogas in Inner Mongolia, China
,
2011
.
[5]
Jiuping Xu,et al.
Biogas as a sustainable energy source in China: Regional development strategy application and decision making
,
2014
.
[6]
Enrico Sciubba,et al.
Emergy and exergy analyses: Complementary methods or irreducible ideological options?
,
2005
.
[7]
B. Bakshi,et al.
Promise and problems of emergy analysis
,
2004
.