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J. Scheduling. 01/2006; 9:153-176.
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European Journal of Operational Research 02/2005; 165(2):339-358. · 1.82 Impact Factor
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J. Log. Algebr. Program. 01/2005; 62:1-39.
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ABSTRACT: This paper deals with the discrete time-cost tradeoff problem (DTCTP) which is well-known to be NP-hard. We propose to compute lower bounds based on Lagrangean relaxation. The basic idea is to decompose the activity-on-node network into subnetworks by relaxing some precedence constraints. Partial solutions provided by the lower bounds are used also to compute upper bounds, that is feasible solutions. Finally, the lower and upper bounds are incorporated into a branch-and-bound algorithm. 1. The Discrete Time-Cost Tradeoff Problem Assume an acyclic activity-on-node network with V = {0, 1, ..., n, n+1} being the set of activities, where 0 is the source and n + 1 is the sink of the network, and V V E being the set of precedence constraints. For each activity V j a set M of duration/cost pairs, so-called modes, is given. For each mode M m , let N jm p denote the processing time of j in mode m and let 0 R jm c denote the cost for performing activity j in mode m. Without loss of gen...
02/2002;
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Networks. 01/1998; 32:85-101.
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ABSTRACT: This paper deals with two most important problems, from both practical and theoretical standpoints, arising in sequencing mixed-model assembly lines. Such lines have become core components of modern repetitive manufacturing, and just-in-time (JIT) manufacturing in particular. One problem is to keep the usage rate of all parts fed into the final assembly as constant as possible (the "level-scheduling problem"), while the other is to keep the line's workstation loads as constant as possible (the "car-sequencing problem"). In this paper the combined problem is formulated as a single-integer programming model. The LP-relaxation of this model is solved by column-generation techniques. The results of an experimental evaluation show that the lower bounds are tight.
Management Science. 47(3):480-491.
