An Enhanced Genetic Algorithm for Assembly Planning

Assembly planning is very important for competitive manufacturing where assemble-to- order of products is in-practice. Assembly planning is a complex task and an optimal assembly plan is detrimental to meet customer demands. This work presents a genetic algorithm for assembly planning. This problem is more difficult than other assembling problems that have already been tackled with success using these approaches, such as the classic Traveling Salesperson Problem (TSP) or the Job Shop Scheduling Problem (JSSP). It not only involves the arranging of tasks, as in those problems, but also the selection of them from a set of alternative operations. Random search methods are being attempted for these types of combinatorial problems. Thus, many current research reports describe efforts to develop more efficient planning algorithms. Genetic algorithms show particular promise for assembly planning. As a result, several recent research reports present assembly planners based upon traditional genetic algorithms. Although prior genetic assembly planners find improved assembly plans with some success, they also tend to converge prematurely at local-optimal solutions. Thus, we present an assembly planner, based upon an enhanced genetic algorithm that demonstrates improved searching characteristics over an assembly planner based upon a traditional genetic algorithm. In particular, our planner finds optimal or near-optimal solutions more reliably and more quickly than an assembly planner that uses a traditional genetic algorithm.

Naini Papers: capacity dilemma

Subject area The subject area of the case is operations management and capacity planning. The case adopts different operation strategies to use the idle capacity. Study level/applicability The case study is suitable for discussion in masters level classes. The case explains the situation of a company which is fighting for its survival. The case reveals the alternative operations strategies it applies to maximize its capacity utilization and reduce its costs. Case overview The case describes a paper producing company which is earning low margins. The company’s capacity remains unused during the off-seasons. The company then plans to share its capacity with another dying industry. Both the companies plan to cooperate and share resources. However, there are other attractive alternatives too and the dilemma situations leave the gap for continuous discussions. Expected learning outcomes The case aims at providing potential alternatives to the students and initiating healthy discussions. The students will be able to understand the capacity utilization dilemmas and applicability of the operations strategy concept in practice. Supplementary materials Teaching notes are available for educators only. Please contact your library to gain login details or email [email protected] to request teaching notes. Subject code CSS 9: Operations and Logistics.