The single machine earliness and tardiness scheduling problem: lower bounds and a branch-and-bound algorithm
نویسندگان
چکیده
منابع مشابه
The single machine earliness and tardiness scheduling problem: lower bounds and a branch-and-bound algorithm*
This paper addresses the single machine scheduling problem with a common due date aiming to minimize earliness and tardiness penalties. Due to its complexity, most of the previous studies in the literature deal with this problem using heuristics and metaheuristics approaches. With the intention of contributing to the study of this problem, a branch-and-bound algorithm is proposed. Lower bounds ...
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A branch-and-bound algorithm for single machine scheduling with quadratic earliness and tardiness penalties
This paper considers the problem of scheduling a single machine, in which the objective function is to minimize the weighted quadratic earliness and tardiness penalties and no machine idle time is allowed. We develop a branch and bound algorithm involving the implementation of lower and upper bounding procedures as well as some dominance rules. The lower bound is designed based on a lagrangian ...
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In one-machine scheduling, MIP time-indexed formulations are often used to provide very good lower bounds through Lagrangian relaxations. In order to get an improved lower bound, we add valid cuts to a time-indexed formulation and show we still have a Lagrangian relaxation that can be solved as a shortest path in a graph. Two branch-and-bound algorithms are then presented for the earliness-tard...
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⎯In this paper, we consider the single machine earliness/tardiness scheduling problem with different release dates and no unforced idle time. The most effective lower bound uses multiplier adjustment procedures that require an initial sequence. We investigate the sensitivity of the lower bounding procedure to the initial sequences, and experiment with different scheduling rules and dominance co...
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ژورنال
عنوان ژورنال: Computational & Applied Mathematics
سال: 2010
ISSN: 1807-0302
DOI: 10.1590/s1807-03022010000200002