TY  - JOUR
AU  - Muenvanichakul, Sirirat 
AU  - Charnsethikul, Peerayuth 
PY  - 2009
TI  - Benders' Decomposition Based Heuristics for Large-Scale Dynamic Quadratic Assignment Problems 
JF  - Journal of Computer Science
VL  - 5
IS  - 1
DO  - 10.3844/jcssp.2009.64.70
UR  - https://thescipub.com/abstract/jcssp.2009.64.70
AB  - Problem statement: Dynamic Quadratic Assignment Problem (DQAP) is NP hard problem. Benders decomposition based heuristics method is applied to the equivalent mixed-integer linear programming problem of the original DQAP. Approach: Approximate Benders Decomposition (ABD) generates the ensemble of a subset of feasible layout for Approximate Dynamic Programming (ADP) to determine the sub-optimal optimal solution. A Trust-Region Constraint (TRC) for the master problem in ABD and a Successive Adaptation Procedure (SAP) were implemented to accelerate the convergence rate of the method. Results: The sub-optimal solutions of large-scales DQAPs from the method and its variants were compared well with other metaheuristic methods. Conclusion: Overall performance of the method is comparable to other metaheuristic methods for large-scale DQAPs.