الفهرس 
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Abstract
Assembly lines have been widely used in various production systems to produce high volume standardized products. An assembly line includes a series of stations arranged along a material handling system. The products are consecutively launched down the line and are moved from station to station. At each station, certain operations are repeatedly performed regarding the cycle time. The decision problem of optimally balancing the assembly work among the stations with respect to some objective is known as the assembly line balancing problem (ALBP). Due to the high level of automation, assembly systems are associated with considerable investment costs. Therefore, the configuration of an assembly line is of critical importance for implementing a cost efficient production system. Configuration planning generally comprises all tasks and decisions which are related to equipping and aligning the productive units for a given production process, before the actual assembly can start. This includes setting the system capacity like the cycle time, the number of stations and the station equipment as well as assigning the tasks to the stations.
A relatively new type of assembly lines is the Mixed-model Two-sided assembly lines. These lines are usually designed to produce high-volume large-sized standardized products, such as automobiles, trucks and buses. These products come in different models and building an assembly line for each model is extremely expensive. Moreover, a two-sided assembly line in practice can provide some advantages over a one-sided assembly line. They provide shorter line length, reduced throughput time, lower cost of tools and fixtures, and less material handling. The ALBP is known to be one of the hard optimization problems as it is proven to be NP-Hard problem. Efforts were diverted to heuristic techniques and algorithms, opting to reach near optimal solutions that can be easily applied.
The aim of this research is to develop a Heuristic Algorithm that is able to solve the Mixed-model Two-sided Assembly Line Balancing Problem (TALBP) with the objective of finding the minimum number of stations as well as the minimum number of mated-stations for a given cycle time. In this research a Genetic Algorithm approach (GA) is presented to solve this balancing problem. The developed algorithm applies a new procedure for generating the initial population and a hybrid crossover and modified scramble mutation operators to effectively search within the solution space. Moreover, due to the TALBP nature a station oriented procedure is formulated for assigning tasks to mated-stations. This procedure specifies new rules that deals with the either tasks rather than assigning these tasks randomly.
In order to run this model, a graphical user interface software was developed that enables the user to solve different types of assembly line balancing problems and tailor define all GA parameters which opens a great room of opportunities of further research on the impact of different parameters.
The effectiveness of the proposed GA operators was evaluated. The proposed method of generating the initial population was tested and a new measure to evaluate the population diversity was introduced. The proposed method was able to generate feasible solutions in different areas of the search space having a more diverse population that yields to better results at the end. Also the applied selection procedure for selecting parents was compared with other procedures used before and it proved its effectiveness in obtaining better solutions. The proposed hybrid crossover operator was tested and proved that it obtains better results than the two-points crossover and precedence preservative crossover when used alone. Also the side assignment rules were proved to be efficient especially in large scale problems.
The developed GA was tested on the available benchmark problems for the Single-model Two-sided Assembly Line Balancing Problems as well as the Mixed-model Two-sided Assembly Line Balancing Problems. For the TALBP the developed GA obtained the best solution for more than 90% of the test problems. As for the Mixed-model TALBP, the GA obtained the best solution for all of the test problems. The results showed that the developed GA was able to find optimum or near optimum solutions within a limited number of iterations.
Finally, a real life case study was implemented to test the applicability of developed algorithm in real life. The results shows that applying the Mixed-model two-sided assembly lines with the right balance will increase the efficiency of the manufacturing system, reduce the cost of handling systems and equipment and reduce the labour cost.