A branch-and-bound method for the fixed charge transportation problem
Management Science
Practical neural network recipes in C++
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Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
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Genetic Algorithms in Search, Optimization and Machine Learning
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Knowledge and Information Systems
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Proceedings of the 2005 ACM symposium on Applied computing
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Journal of Heuristics
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Journal of Heuristics
Algorithms for solving the single-sink fixed-charge transportation problem
Computers and Operations Research
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
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Applied Soft Computing
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IEEE Transactions on Evolutionary Computation
Expert Systems with Applications: An International Journal
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This paper proposes a genetic algorithm (GA) based heuristic to the multi-period fixed charge distribution problem associated with backorder and inventories. The objective is to determine the size of the shipments, backorder and inventories at each period, so that, the total cost incurred during the entire period towards transportation, backorder and inventories is minimum. The model is formulated as pure integer nonlinear programming and 0-1 mixed integer linear programming problems, and proposes a GA based heuristic to provide solution to the above problem. The proposed GA based heuristic is evaluated by comparing their solutions with lower bound, LINGO solver and approximate solutions. The comparisons reveal that the GA generates better solutions than the approximate solutions, and is capable of providing solutions equal to LINGO solutions and closer to the lower bound value of the problems.