Note—Operations Sequencing in Discrete Parts Manufacturing
Copyright policy )Note—Operations Sequencing in Discrete Parts Manufacturing
This paper presents an algorithm for efficiently sequencing the cutting operations associated with the manufacture of discrete parts on a CNC machine. The problem is first modeled as an integer program but recast via Lagrangian relaxation as a min-cut problem on a bipartite network. Tight lower bounds are obtained with a max-flow algorithm. The corresponding solution is used as input to a greedy heuristic which generates “good” feasible points. Given nonconvergence, a branch and bound strategy is used to find the optimal solution.
- Applied Research Laboratories, The University of Texas at Austin United States
- The University of Texas at Austin United States
bipartite network, Lagrangian relaxation, flexible manufacturing systems, integer programming, Lagrangian relaxation, branch and bound, computer-aided process planning, Deterministic scheduling theory in operations research, cutting operations, Integer programming, sequencing, max-flow algorithm, greedy heuristic, Numerical mathematical programming methods, branch and bound, Deterministic network models in operations research, Production models, computer-aided process planning
bipartite network, Lagrangian relaxation, flexible manufacturing systems, integer programming, Lagrangian relaxation, branch and bound, computer-aided process planning, Deterministic scheduling theory in operations research, cutting operations, Integer programming, sequencing, max-flow algorithm, greedy heuristic, Numerical mathematical programming methods, branch and bound, Deterministic network models in operations research, Production models, computer-aided process planning
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