Abstract
Cost optimization is one of the most important issues in distribution operations of any manufacturing system. Most real life problems are non-deterministic polynomial-time hard, and solving such pr...
Highlights
Transhipment of goods in manufacturing settings is a crucial task especially in developing nations
We developed artificial neural network (ANN) model for effective product distribution in a dual-source multidestination system for a paint manufacturing company in Nigeria
The result obtained for mean square error (MSE) and R-values of the data-set with 15 samples, from the first iteration is shown in Table 2 and Figure 7
Summary
Transhipment of goods in manufacturing settings is a crucial task especially in developing nations. It becomes necessary to develop models and algorithms as well as plans that are suitable for effective product distribution at optimal cost. Solving transhipment problems is much more difficult than transportation model because transhipment allows flow through intermediate points. This is so if the input are stochastic or fuzzy. The major challenge manufacturers’ face in industries today is how to consistently meet customers’ requirements and demands at an optimal cost with the ability to effectively compete in the market. These require the optimization of production processes and the distribution operations. In view of the practical effectiveness of optimization problems there is a need for efficient and robust computational algorithms which can unravel these problems arising in different fields
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