Solving super-large-scale management optimization problem: A case study on urban communities scheduling for excremental residue collecting and transporting

The urban communities scheduling for excremental residue collecting and transporting in Luohu District, Shenzhen City is a super-large-scale management optimization problem. Taking this realistic problem as a case, this paper explored the feasible solving approach to this type of super-large-scale optimization problem. A model of urban communities scheduling for excremental residue collecting and transportation was established. According to the so-called greedy rule, a heuristic algorithm based on constructive rule was proposed to solve the model, whose validity was inspected through small-scale numerical examples. The proposed algorithm was applied to solve the realistic problem coming from the case, and a satisfactory scheduling scheme was generated. This study shows that, to solve a realistic super-large-scale optimization problem, an appropriate heuristic algorithm in which the simplest greedy rule and the intrinsic characteristics of the problem are incorporated, might be applicable. This study provides an alternative solving approach to the similar super-large-scale optimization problems.