Genetic algorithms for nonlinear 0-1 programming problems in operational planning of district heating and cooling plants

In recent years, the operational planning of a district heating and cooling plant has been arousing interest as a result of development of cooling load prediction methods for district heating and cooling systems. In this paper, we formulate an operational planning problem of a district heating and cooling plant as a nonlinear 0-1 programming problem. Realizing that there does not exist an efficient exact solution method and the problem involves hundreds of variables, we propose an approximate solution method using genetic algorithms for the formulated nonlinear 0-1 programming problem. Furthermore, we investigate the feasibility and effectiveness of the proposed method for an operational planning problem of an actual district heating and cooling plant.