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da Silva, Felipe Augusto Moreira; Moretti, Antonio Carlos; de Azevedo, Anibal Tavares (2013)
Publisher: Hindawi Publishing Corporation
Languages: English
Types: Article
Subjects: Mathematics, QA1-939, Article Subject
This paper addresses a scheduling problem in an actual industrial environment of a baking industry where production rates have been growing every year and the need for optimized planning becomes increasingly important in order to address all the features presented by the problem. This problem contains relevant aspects of production, such as parallel production, setup time, batch production, and delivery date. We will also consider several aspects pertaining to transportation, such as the transportation capacity with different vehicles and sales production with several customers. This approach studies an atypical problem compared to those that have already been studied in literature. In order to solve the problem, we suggest two approaches: using the greedy heuristic and the genetic algorithm, which will be compared to small problems with the optimal solution solved as an integer linear programming problem, and we will present results for a real example compared with its upper bounds. The work provides us with a new mathematical formulation of scheduling problem that is not based on traveling salesman problem. It considers delivery date and the profit maximization and not the makespan minimization. And it also provides an analysis of the algorithms runtime.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Gantt, H. L.. Work, Wages, and Profits. 1916
    • Johnson, S. M.. Optimal two- and three-stage production schedules with setup times included. Naval Research Logistics Quarterly. 1954; 1 (1): 61-68
    • Bellman, R.. The theory of dynamic programming. Bulletin of the American Mathematical Society. 1954; 60 (6): 503-515
    • Lomnicki, Z. A.. A branch-and-bound algorithm for the exact solution of the three-machine scheduling problem. Operational Research Quarterly. 1965; 16: 89-100
    • Ignall, E., Schrage, L.. Application of the branch -and-bound technique to some flowshop scheduling problems. Operations Research. 1965; 13 (3): 400-412
    • Little, J. D. C., Murty, K. G., Sweeney, D. W., Karel, C.. An algorithm for the traveling salesman problem. Operations Research. 1963; 11 (6): 972-989
    • Garey, M. R., Johnson, D. S., Sethi, R.. The complexity of flowshop and jobshop scheduling. Mathematics of Operations Research. 1976; 1 (2): 117-129
    • Sridhar, J., Rajendran, C.. Scheduling in a cellular manufacturing system: a simulated annealing approach. International Journal of Production Research. 1993; 31 (12): 2927-2945
    • Rajendran, C., Ziegler, H.. Heuristics for scheduling in flowshops and owline-based manufacturing cells to minimize the sum of weighted owtime and weighted tardiness of jobs. Computers & Industrial Engineering. 1999; 37 (4): 671-690
    • Schaller, J. E., Gupta, J. N. D., Vakharia, A. J.. Scheduling a flowline manufacturing cell with sequence dependent family setup times. European Journal of Operational Research. 2000; 125 (2): 324-339
    • Schaller, J.. A new lower bound for the flow shop group scheduling problem. Computers & Industrial Engineering. 2001; 41 (2): 151-161
    • França, P. M., Gupta, J. N. D., Mendes, A. S., Moscato, P., Veltink, K. J.. Evolutionary algorithms for scheduling a flowshop manufacturing cell with sequence dependent family setups. Computers & Industrial Engineering. 2005; 48 (3): 491-506
    • Hendizadeh, S. H., Faramarzi, H., Mansouri, S. A., Gupta, J. N. D., ElMekkawy, T. Y.. Meta-heuristics for scheduling a flowline manufacturing cell with sequence dependent family setup times. International Journal of Production Economics. 2008; 111 (2): 593-605
    • Croce, F. D., Tadei, R., Volta, G.. A genetic algorithm for the job shop problem. Computers & Operations Reseach. 1995; 22 (1): 15-24
    • Adams, J., Balas, E., Zawack, D.. The shifting bottleneck procedure for job shop scheduling. Management Science. 1988; 34 (3): 391-401
    • Dagli, C. H., Sittisathanchai, S.. Genetic neuro-scheduler: a new approach for job shop scheduling. International Journal of Production Economics. 1995; 41 (1–3): 135-145
    • Arthanari, T. S., Ramaswamy, K. G.. An extension of two machine sequencing problem. Operation Research. 1971; 8: 10-22
    • Brah, S. A., Hunsucker, J. L.. Branch and bound algorithm for the flowshop with multiple processors. European Journal of Operational Research. 1991; 51 (1): 88-99
    • Sawik, T. J.. A scheduling algorithm for flexible flow lines with limited intermediate buffers. Applied Stochastic Models and Data Analysis. 1993; 9 (2): 127-138
    • Ding, F.-Y., Kittichartphayak, D.. Heuristics for scheduling flexible flow lines, computers. Industrial Engineering. 1994; 26 (1): 27-34
    • Guinet, A., Solomon, M. M., Kedia, P. K., Dussauchoy, A.. A computational study of heuristics for two-stage flexible flowshops. International Journal of Production Research. 1996; 34 (5): 1399-1415
    • Nowicki, E., Smutnicki, C.. The flow shop with parallel machines: a tabu search approach. European Journal of Operational Research. 1998; 106 (2-3): 226-253
    • Cormen, T. H., Leiserson, C. E., Rivest, R. L., Stein, C.. Greedy algorithms. Introduction to Algorithms. 2001: 379-399
    • Bendall, G., Margot, F.. Greedy type resistance of combinatorial problems. Discrete Optimization. 2006; 3 (4): 288-298
    • Applegate, D. L., Bixby, R. E., Chvatal, V., Cook, W. J.. The Travelling Salesman Problem: A Computational Study. 2006
    • Allahverdi, A., Ng, C. T., Cheng, T. C. E., Kovalyov, M. Y.. A survey of scheduling problems with setup times or costs. European Journal of Operational Research. 2008; 187 (3): 985-1032
    • da Silva, F. A. M.. The application of scheduling in the industry [M.S. dissertation]. 2011
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