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Home  >  Volume 35

Minimization of Changeover Time in a Brewery Company Using Ant Colony Optimization by P.E. Amiolemhen and J. Akpomwomwo (pages 155-162)
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Abstract

This study utilizes Ant Colony Optimization (ACO) approach in solving the asymmetric travelling Salesman problem (aSTP) of a brewery company in Nigeria with a view to minimizing the total Changeover Setup time and obtaining an optimal schedule or schedules.

The acquired secondary data covering the 2013/2014 production year including the peak periods from January to April and August to December was analyzed to determine the expected changeover time. The expected changeover time for the sequence of Stock keeping unit (sku) was then formulated as a Travelling salesman (TSP) matrix, and Branch and bound Method (B&B) of solution was employed to determine a lower bound for the tour, as well as the optimal sequence. Afterward, Ant Colony Optimization (ACO) was applied to obtain possible optimal tours. The Ant algorithm formulated as a program in Matlab 7.5 environment, was used to solve the TSP. 

The Ant system algorithm found (after 500 iterations) an optimal route of length 1126.5 Minutes {or 18.78 Hours} in three different parameters settings: parameters α=1, β=3, two alternate optimal sequence ; parameters α=2, β=3, four optimal sequence  and parameters α=2, β=4, six optimal sequence returned respectively. The optimal sequence result common to these three parameters setting is :  1-3-8-9-5-2-6-4-7-1 [Grand Beer – Castle Stout – Grand Malt – Beta Malt – Redds Beer – Castle Beer – Trophy Beer – Eagle Beer – Hero Beer –Grand Malt]. The total pairwise distance of the Optimal Sequence of the Branch and Bound method when computed from the formulated Cost matrix of is 1126.75 Minutes and this is also close to the sub-optimal tour Length of the Ant System Algorithm (AS). Finally, the optimal tour length of 1126.5 Minutes generated by the ACO make this model a success.

Keywords: Ant Colony Optimization (ACO), Branch and bound (B&B) Method, Travelling salesman Problem (TSP), Scheduling, Branch and bound, Optimal Tour

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