We present and compare a number of branch and bound algorithms for minimizing the total weighted tardiness in job shops. There are basically two types of branching schemes. The first one inserts operations in a partial schedule, while the second one fixes arcs ' in the disjunctive graph formulation of the problem. The bounding schemes are based on the analysis of precedence constraints, and on the solution of nonpreemptive single machine subproblems that are subject to so-called delayed precedence constraints. We obtain optimal solutions for all the instances with ten jobs and ten machines that we consider, including three tardiness versions of a well-known 10 x 10 instance introduced by Muth and Thompson 111 in 1963.
Abstract:We present a shifting bottleneck heuristic for minimizing the total weighted tardiness in a job shop. The method decomposes the job shop into a number of single-machine subproblems that are solved one after another. Each machine is scheduled according to the solution of its corresponding subproblem. The order in which the single machine subproblems are solved has a significant impact on the quality of the overall solution and on the time required to obtain this solution. We therefore test a number of different orders for solving the subproblems. Computational results on 66 instances with ten jobs and ten machines show that our heuristic yields solutions that are close to optimal, and it clearly outperforms a well-known dispatching rule enhanced with backtracking mechanisms.
Scientific literature reports scarce evidence of whether Internetbased procurement systems improve the efficiency of State purchases. We propose a methodology to estimate savings in: (i) the centralization of administrative tasks, and (ii) price differentials due to a larger number of contractors and suppliers bidding on contracts. We test our methods with ChileCompra, the Chilean e-procurement agency. During 2007, 885 Chilean State agencies used this system to purchase US$4.5 billion in products and services. Our preliminary results show price reductions of 2.65% and administrative cost savings of 0.28%-0.38% between 2006 and 2007.3) Reduce administrative cost by improving the procurement process; and ----------------------------
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