Consultant assignment and routing problem with priority matching

Abstract

The consultant assignment and routing problem is to simultaneously assign consultant supplies to client demands and determine the best traveling routes for consultants. Constraints to be considered include skill requirement, capacity limitation, fixed demand, and a maximum number of travel legs. This paper further takes into consideration priority matching, which restricts that clients can only be assigned to consultants with appropriate priority levels. In order to solve this problem, we present a decomposition algorithm named RMIP and a MIP-based neighborhood search algorithm. In addition, we extend an existing MILP formulation and compare our algorithms with it. The effectiveness and efficiency of the proposed algorithms are evaluated on a hundred synthetic instances and twelve real-life instances. Computational results show that the modified MILP formulation is only suitable for solving small-scale instances and a part of the medium-scale instances. For large-scale and real-life instances, the proposed two algorithms are significantly superior to the MILP formulation in solution quality and computational time.