Single-facility resource allocation under capacity-based economies and diseconomies of scope

Article Abstract:

The problem of optimal resource allocation in a single-facility production environment with capacity-based economies and diseconomies is considered. The resulting model, SCOPE, is a generalization of the 0-1 collapsing knapsack problem. It characterizes capacity-based economies and diseconomies as being determined by the number of tasks assigned to the facility. An allocation model, GENCAP, is also developed, which generalizes SCOPE and models nonlinear capacity interaction as dependent on the specific set of jobs loaded into the facility. Tabu-search heuristics and branch-and-bound algorithms are formulated to solve the two problems. Extensive computational testing shows the effectiveness of both solution procedures. The analysis also demonstrates the tractability of problems with nonlinear capacity behavior.

Production management

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New benchmark results for the resource-constrained project scheduling problem

Article Abstract:

A revision and extension of the efficient depth-first branch-and-bound procedure developed by Demeulemeester and Herroelen (1992) to address the resource-constrained project scheduling problem (RCPSP) was conducted. This new DH-procedure makes use of the advances in 32-bit programming found in Microsoft Visual C++ 2.0 compilers under Windows NT 3.50. The new code increased speed by a factor of approximately three on the 110 Patterson problems and, more significantly, facilitated the optimal solution of the 480 Kolisch, Sprecher and Drexl (KSD) instances. This proved that the actual bottleneck was occurring in addressable computer memory. In addition, it allowed for the solution of the remaining problem of KSD 291 within three hours of computation time. These represent a fresh benchmark for the RCPSP.

Prepackaged software, Software Publishers, Computer Language Software ex Military, Branch and bound algorithms, Compilers (Software), Compilers

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Scheduling of project networks by job assignment

Article Abstract:

The project management problem of the cost-effective allocation of sparse resources to the different jobs making up the project is examined. This time-resource-cost-tradeoff problem is studied using a combination of brand and bound/dynamic programming algorithm, together with the Monte Carlo stochastic scheduling technique. Computational results are discussed.

Stochastic processes, Monte Carlo method, Monte Carlo methods

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