Introducing a Hybrid Genetic Algorithm for Integration of Set Up and Process Planning

Sai Ho Chung, Tung Sun Chan

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review


Scheduling problems are easily found in real life situations such as publishing houses, hospitals and airports. Production scheduling is one of the most difficult problems that significantly affect the production planning system. Traditionally, a production manager makes decisions on production planning, especially scheduling, with his intuition, experience, and judgment. However, the difficulty of determining a good production schedule increases along with the problem scale. As a result, nowadays, various optimization techniques and information systems have been developed to improve scheduling in production planning. In solving production scheduling problems, Genetic Algorithms (GAs) are an efficient optimization method based on the evolutionary computing paradigm that has emerged in recent years. GAs can obtain near optimal (or sometimes optimal) solutions from large solution spaces for many different engineering problems, especially in practical environments. This chapter introduces a hybrid genetic algorithm to deal with practical production scheduling problems. The studied production models are subject to capacity constraints, precedence relationships, and alternative machining with different processing times. More importantly, we will take into consideration the processing time, transportation time between resources, and especially machine set-up time between different processes. The introduced hybrid genetic algorithm is demonstrated through some examples for minimizing the makespan of a set of given tasks.
Original languageEnglish
Title of host publicationEvolutionary Computing in Advanced Manufacturing
PublisherJohn Wiley and Sons
Number of pages14
ISBN (Print)9780470639245
Publication statusPublished - 22 Aug 2011


  • Hybrid genetic algorithm
  • Makespan
  • Process planning
  • Scheduling
  • Set-up time

ASJC Scopus subject areas

  • General Engineering


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