Abstract
In this paper, a hybrid flow shop scheduling problem with a new approach considering time lags and sequence-dependent setup time in realistic situations is presented. Since few works have been implemented in this field, the necessity of finding better solutions is a motivation to extend heuristic or meta-heuristic algorithms. This type of production system is found in industries such as food processing, chemical, textile, metallurgical, printed circuit board, and automobile manufacturing. A mixed integer linear programming (MILP) model is proposed to minimize the makespan. Since this problem is known as NP-Hard class, a meta-heuristic algorithm, named Genetic Algorithm (GA), and three heuristic algorithms (Johnson, SPTCH and Palmer) are proposed. Numerical experiments of different sizes are implemented to evaluate the performance of presented mathematical programming model and the designed GA in compare to heuristic algorithms and a benchmark algorithm. Computational results indicate that the designed GA can produce near optimal solutions in a short computational time for different size problems.
Highlights
Among the production scheduling systems, hybrid flow shops scheduling (HFS) problem is one of the most distinguishable environments demonstrating numerous applications in real industrial settings [16]
Various heuristics have been developed for a scheduling hybrid flow shop without time lags and can be classified in several categories
The hybrid flow shop scheduling which considers some real constraints in real world and a formulation as well as an integer linear programming mathematical model is presented
Summary
Among the production scheduling systems, hybrid flow shops scheduling (HFS) problem is one of the most distinguishable environments demonstrating numerous applications in real industrial settings [16]. In HFS, we have a set of n jobs and a set of g production stages owning several identical machines operating in parallel. Many restrictions to the previous assumptions can be enforced in manufacturing industries due to modeling system in a more realistic method, such as minimum or maximum time lags between two successive operations, setup times which are either sequence-dependent or not, limited buffer capacity between two successive stages. A hybrid flow shop scheduling problem with a new approach considering time lags and sequence-dependent setup time in realistic situations is presented. Farahmand-Mehr et al.: Manufacturing Rev. 2014, 1, 21 have been implemented in this field, the necessity of finding better solutions is a motivation to extend heuristic or meta-heuristic algorithms This type of production system is found in industries such as food processing, chemical, textile, metallurgical, printed circuit board, and automobile manufacturing.
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