76 research outputs found
APPROXIMATE ANALYSIS OF RE-ENTRANT LINES WITH BERNOULLI RELIABILITY MODELS
Re-entrant lines are widely used in many manufacturing systems, such as semiconductor, electronics, etc. However, the performance analysis of re-entrant lines is largely unexplored due to its complexity. In this thesis, we present iterative procedures to approximate the production rate of re-entrant lines with Bernoulli reliability of machines. The convergence of the algorithms, uniqueness of the solution, and structural properties, have been proved analytically. The accuracy of the procedures is investigated numerically. It is shown that the approaches developed can either provide a lower bound or a closed estimate of the system production rate. Finally, a case study of automotive ignition component line with re-entrant washing operations is introduced to illustrate the applicability of the method. The results of this study suggest a possible route for modeling and analysis of re-entrant systems
Makespan Minimization in Re-entrant Permutation Flow Shops
Re-entrant permutation flow shop problems occur in practical applications such as wafer manufacturing, paint shops, mold and die processes and textile industry. A re-entrant material flow means that the production jobs need to visit at least one working station multiple times. A comprehensive review gives an overview of the literature on re-entrant scheduling. The influence of missing operations received just little attention so far and splitting the jobs into sublots was not examined in re-entrant permutation flow shops before. The computational complexity of makespan minimization in re-entrant permutation flow shop problems requires heuristic solution approaches for large problem sizes. The problem provides promising structural properties for the application of a variable neighborhood search because of the repeated processing of jobs on several machines. Furthermore the different characteristics of lot streaming and their impact on the makespan of a schedule are examined in this thesis and the heuristic solution methods are adjusted to manage the problem’s extension
The dynamic, resource-constrained shortest path problem on an acyclic graph with application in column generation and literature review on sequence-dependent scheduling
This dissertation discusses two independent topics: a resource-constrained shortest-path problem
(RCSP) and a literature review on scheduling problems involving sequence-dependent setup
(SDS) times (costs).
RCSP is often used as a subproblem in column generation because it can be used to
solve many practical problems. This dissertation studies RCSP with multiple resource
constraints on an acyclic graph, because many applications involve this configuration, especially
in column genetation formulations. In particular, this research focuses on a dynamic RCSP
since, as a subproblem in column generation, objective function coefficients are updated using
new values of dual variables at each iteration. This dissertation proposes a pseudo-polynomial
solution method for solving the dynamic RCSP by exploiting the special structure of an acyclic
graph with the goal of effectively reoptimizing RCSP in the context of column generation. This
method uses a one-time âÂÂpreliminaryâ phase to transform RCSP into an unconstrained shortest
path problem (SPP) and then solves the resulting SPP after new values of dual variables are used
to update objective function coefficients (i.e., reduced costs) at each iteration. Network
reduction techniques are considered to remove some nodes and/or arcs permanently in the preliminary phase. Specified techniques are explored to reoptimize when only several
coefficients change and for dealing with forbidden and prescribed arcs in the context of a column
generation/branch-and-bound approach. As a benchmark method, a label-setting algorithm is
also proposed. Computational tests are designed to show the effectiveness of the proposed
algorithms and procedures.
This dissertation also gives a literature review related to the class of scheduling
problems that involve SDS times (costs), an important consideration in many practical
applications. It focuses on papers published within the last decade, addressing a variety of
machine configurations - single machine, parallel machine, flow shop, and job shop - reviewing
both optimizing and heuristic solution methods in each category. Since lot-sizing is so
intimately related to scheduling, this dissertation reviews work that integrates these issues in
relationship to each configuration. This dissertation provides a perspective of this line of
research, gives conclusions, and discusses fertile research opportunities posed by this class of
scheduling problems.
since, as a subproblem in column generation, objective function coefficients are updated using
new values of dual variables at each iteration. This dissertation proposes a pseudo-polynomial
solution method for solving the dynamic RCSP by exploiting the special structure of an acyclic
graph with the goal of effectively reoptimizing RCSP in the context of column generation. This
method uses a one-tim
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