Experiments with parallel algorithms for combinatorial problems

In the last decade many models for parallel computation have been proposed and many parallel algorithms have been developed. However, few of these models have been realized and most of these algorithms are supposed to run on idealized, unrealistic parallel machines. The parallel machines constructed so far all use a simple model of parallel computation. Therefore, not every existing parallel machine is equally well suited for each type of algorithm. The adaptation of a certain algorithm to a specific parallel archi- tecture may severely increase the complexity of the algorithm or severely obscure its essence. Little is known about the performance of some standard combinatorial algorithms on existing parallel machines. In this paper we present computational results concerning the solution of knapsack, shortest paths and change-making problems by branch and bound, dynamic programming, and divide and conquer algorithms on the ICL-DAP (an SIMD computer), the Manchester dataflow machine and the CDC-CYBER-205 (a pipeline computer)

Local search in physical distribution management

Physical distribution management presents a variety of decision making problems at three levels of strategic, tactical and operational planning. The importance of effective and efficient distribution management is evident from its associated costs. Physical distribution management at the operational level, which is considered in this paper is responsible for an important fraction of the total distribution costs. Not surprisingly, there is a growing demand for planning systems that produce economical routes. Enormous theoretical as well as practical advances have been made, in the last decade. Some of the resulting vehicle and scheduling models will be discussed in this paper, like vehicle routing problem with time window and the pickup and delivery problem with time window