Genetic algorithm approach to earliness and tardiness production scheduling and planning problem

Article Abstract:

Genetic algorithm (GA) approach works effectively and efficiently in solving the problem of earliness and tardiness production scheduling and planning (ETSP). It is capable of finding solutions to difficult and non-linear function of the measure performance. The approach, which utilizes lot-size consideration and capacity balancing issues, also works well on severe ETPSP problem with various product types. It does not need any unjustifiable perceptions on the objective functions, such as linearity, convexity and differentiability.

Research and Development in the Physical, Engineering, and Life Sciences, Mathematics, Analysis, Algorithms

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Application of calculus of variations to a continuous time aggregate production model

Article Abstract:

Initial studies on the production problem of balancing inventory and production costs in continuous-time frame assumed linear inventory holding costs and a proportional relationship between costs and rates of production. A model extends the analysis to include the effects of discrete time variables in overtime and hiring-firing costs with calculus of variations. An optimal trajectory was generated that defined combinations corresponding to Kuhn-Tucker conditions.

Inventory control

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