A multi-objective optimization problem for using poultry litter in electricity production

Business School, Guangdong University of Foreign Studies, Guangzhou, China
Louisiana State University (LSU) and LSU Agricultural Center, Baton Rouge, LA, USA
South China Ag University, Guangzhou, China


Two objectives (profit maximization and pollution minimization) are optimized.

A location-allocation problem.

A three-stage heuristic algorithm.

Different initiating strategies for reactors’ locations.

Real-world data from Louisiana, USA.


We use a location allocation model to solve multi-objective functions where poultry litter is used to produce electricity, and the objectives are to maximize the profit and minimize the total CO2 equivalent emission. A three-stage heuristic algorithm consisting of location initialization, second order conic programming, and linear programming models is used to find the Pareto optimal solution for the multi-objective problem. Constant initial location, random updating, and k-means clustering strategies are applied for updating the initial locations of the reactor(s). Practical findings, including the location and allocation strategies, are developed for poultry litter use in electricity production in the state of Louisiana, USA. Results show that building a reactor without capacity limit capable of utilizing the entire surplus poultry litter from the surrounding farms is not only economically inefficient, but is also environmentally detrimental. The emission preference coefficient in the multi-objective problem with capacity constraint is found to dramatically affect the allocation strategy when the coefficient exceeds a certain threshold. In general, location-allocation solutions for multiple reactors with capacity constraint are found to be economically and environmentally superior. Different initiating and updating strategies for the reactor’s location(s) significantly affect the solution values, especially when more than one objective is considered.


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