Browsing by Subject "Assembly Line Balancing"

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Open Access
Assembly line balancing using genetic algorithms
(1997) Tanyer, Muzaffer
For the last few decades, the genetic algorithms (GAs) have been used as a kind of heuristic in many areas of manufacturing. Facility layout, scheduling, process planning, and assembly line balancing are some of the areas where GAs are already popular. GAs are more efficient than traditional heuristics and also more flexible as they allow substantial changes in the problem’s constraints and in the solution approach with small changes in the program. For this reason, GAs attract the attention of both the researchers and practitioners. Chromosome structure is one of the key components of a GA. Therefore, in this thesis, we focus on the special structure of the assembly line balancing px'oblem and design a chromosome structure that operates dynamically. We propose a new mechanism to work in parallel with GAs, namely dynamic partitioning. Different from many other GA researchers, we particularly compare different population re\asion mechanisms and the effect of elitism on these mechanisms. Elitism is revised by the simulated annealing idea and various levels of elitism are created and their effects are observed. The proposed GA is £ilso compared with the traditional heuristics.
Open Access
Balancing straight and U-Type assembly lines with stochastic process times
(2003) Şekerci, Halil
In this thesis, we study the problem of assembly line balancing with stochastic task process times. The research considers both the well-known straight line balancing problem and U-line balancing problem where the line is paced, with no buffer inventories between stations. The objective is to minimize a two component cost function where the cost terms come from cost of manning the line and cost of finishing the incomplete units off the line. Cost is measured by an existing exact method for straight line balancing and a heuristic cost measurement method is developed for U-line balancing. The key idea in the core of this research is a task's marginal desirability for assignment at a given station. This idea is embedded in a beam search heuristic for solving both the straight line and U-line balancing problem. Extensive computational experiments and simulation experiments are made with well-known problems in the literature under the assumption of normally distributed task processing times. The quality of the solutions found by beam search for the straight-line balancing problem is compared to an existing method in literature. A simulation model of the assembly design is constructed and sample results from the U-line balancing problem are tested against the simulation results. The algorithm presented in this thesis improves the objective function by up to 24 percent.