In many logistic environments, managers must make decisions such as facility location and distribution planning. Though this interdependence between the two decisions has been recognized and an extensive body of combined location-routing literature has developed in less than 30 years, simultaneous solution methods are limited to heuristics due to the problem complexity. This paper proposes a two-phase hybrid heuristic search approach, which decomposes the location-routing problem into a location-allocation problem and a vehicle routing problem. The two-phase approach aims to integrate two levels of decision making (location and routing) in a computationally efficient manner. In the location phase of the algorithm, a tabu search is performed on the location variables to determine a good configuration of facilities to be used in the distribution. For each of the location configurations, ant colony algorithm is run on the routing variables in order to obtain a good routing for the given configuration. In the routing phase of the algorithm, the large problem can be furthermore decomposed into the much smaller sub-problems. The approach does not only improve the efficiency, but also improves the effectiveness of the algorithm. The results indicate that this method performs well in terms of the solution quality and run time consumed.