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Applications to be executed in grid computing environments become more and more complex and usually consist of multiple interdependent tasks. The coordinated execution of such tightly or loosely coupled tasks often requires simultaneous access to different grid resources. This leads to the problem of resource co-allocation. Efficient and robust scheduling algorithms have to be developed that can cope with the Grid's large- scale distribution, a high number of competing and demanding applications, the inherent resource heterogeneity and the often limited view on resource availability. In this paper, we present two heuristic scheduling algorithms that are based on a well-known list scheduling algorithm and both support co- allocation and advance resource reservation. Our first algorithm preserves the run-time efficiency of greedy list schedulers while the second approach incorporates more sophisticated search techniques in order to achieve better results with respect to the performance metrics. Both algorithms have been implemented within a grid simulation framework. An extensive simulation study was conducted to evaluate and compare the performance of both algorithms. It showed the general suitability of our enhanced list scheduling heuristics within heterogeneous grid environments.