Handling the assembly line balancing problem in the clothing industry using a genetic algorithm

Abstract

Assembly line balancing problems that occur in real world situations are dynamic and are fraught with various sources of uncertainties such as the performance of workers and the breakdown of machinery. This is especially true in the clothing industry. The problem cannot normally be solved deterministically using existing techniques. Recent advances in computing technology, especially in the area of computational intelligence, however, can be used to alleviate this problem. For example, some techniques in this area can be used to restrict the search space in a combinatorial problem, thus opening up the possibility of obtaining better results. Among the different computational intelligence techniques, genetic algorithms (GA) is particularly suitable. GAs are probabilistic search methods that employ a search technique based on ideas from natural genetics and evolutionary principles. In this paper, we present the details of a GA and discuss the main characteristics of an assembly line balancing problem that is typical in the clothing industry. We explain how such problems can be formulated for genetic algorithms to solve. To evaluate the appropriateness of the technique, we have carried out some experiments. Our results show that the GA approach performs much better than the use of a greedy algorithm, which is used by many factory supervisors to tackle the assembly line balancing problem.

Mathematical model and genetic optimization for the job shop scheduling problem in a mixed- and multi-product assembly environment: A case study based on the apparel industry

“…Tomastik, Luh, and Liu (1996) developed a low-order integer programming model using the Lagrangian relaxation method which integrated scheduling and resource allocation for a flexible manufacturing system. Chan, Hui, Yeung, and Ng (1997) used a GA to solve an assembly line balancing problem in the apparel industry and concluded that the GA was an appropriate tool to solve the dynamic and complex production scheduling problem. Wong, Mok, and Leung (2005) also developed a GA to balance an apparel assembly line of UPS and investigated the impact of different level of skill inventory on the assembly makespan.…”

A Using the Fuzzy Logic to Classify Vietnamese Women’s Shapes from 6 to 18 Years Old

“…Các chi tiết được quy về hình chữ nhật để sắp xếp trước khi cắt, với chiều dài cuộn vải được giả định là không giới hạn. Trong vấn đề thiết kế chuyền may có đề tài của nhóm tác giả Chan và cs, Chen và cs đã sử dụng thuật toán di truyền GA để thiết lập cân bằng chuyền 13,14 . Đề tài của Chang và cs đã sử dụng thuật toán GA để phát triển một hệ thống hỗ trợ quyết định cho sản xuất hàng may mặc 15 .…”

A hybrid genetic algorithm approach for solving an extension of assembly line balancing problem

“…For example, Chan et al (1998) developed a GA to solve SMALB Type-1 problem in the clothing industry in order to maximise line efficiency. For example, Chan et al (1998) developed a GA to solve SMALB Type-1 problem in the clothing industry in order to maximise line efficiency.…”