A Solution Method for Comprehensive Solution Candidates in Dynamic Production Planning by Zero-Suppressed Binary Decision Diagrams

Abstract

Dynamic changes as machine breakdowns make current production plan infeasible and inaccurate. The influence of dynamic changes spread to whole production planning that consists of several domains such as process planning, production scheduling and so on. In this study, solution space in the production planning is defined as comprehensive. We have applied Zero-Suppressed Binary Decision Diagrams (ZDDs) for the representation of solution candidates that satisfy constraints between such domains so for. In dynamic production planning problems, manufacturing achievements and dynamic changes may make solution space change. In this paper, we define such events as constraints for ZDDs and propose an approach to update the ZDD to deal with the events. Moreover,we propose a genetic algorithm (GA) to find solutions in the ZDD. Experimental results demonstrate that the proposed approach to address such event with ZDDs and the GA are effriciently used to solve the dynamic production planning problem.