Exact solution methods for a generalized assignment problem with location/allocation considerations

Abstract

We investigate modeling approaches and exact solution methods for a generalized assignment problem with location/allocation (GAPLA) considerations. In contrast with classical generalized assignment problems, each knapsack in GAPLA is discretized into consecutive segments having different levels of attractiveness. To maximize a total reward function, the decision maker decides not only about item knapsack assignments, but also the specific location of items within their assigned knapsacks and their total space allocation within prespecified lower and upper bounds. Mathematical programming formulations are developed for single and multiple knapsack variants of this problem along with valid inequalities, preprocessing routines, and model enhancements. Further, a branch-and-price algorithm is devised for a set partitioning reformulation of GAPLA, and is demonstrated to yield substantial computational savings over solving the original formulation using branch-and-bound/cut solvers such as CPLEX over challenging problem instances. 2016 INFORMS.