The implementation of milk-run in Indonesia has been started since 2005. As a developing

country, there is a challenge to operate milk-run smoothly especially in urban area due to

severe traffic congestion and unfavourable road condition in some areas. This research aimed

to analyze the practice of milk-run operation in one of the biggest Japanese automotive

companies in Indonesia. Transportation Value Stream Mapping (TVSM) is applied in order

to perform just-in-time delivery in the supply chain before operating milk-run. It is discussed

that this company still need to continue in improving milk-run operation. The operation

system needs control and integration from manufacturer, supplier and logistics partner.

The advantage of milk-run operation is cost reduction and also support green logistics in

decreasing emission of carbondioxide (CO2) by reducing the number of trucks used.

The objective of the milk-run design problem considered in this paper is to minimize transportation

and inventory costs by manipulating fleet size and the capacity of vehicles and

storage areas. Just as in the case of an inventory routing problem, the goal is to find a periodic

distribution policy with a plan on whom to serve, and how much to deliver by what

fleet of tugger trains travelling regularly on which routes. This problem boils down to determining

the trade-off between fleet size and storage capacity, i.e. the size of replenishment

batches that can minimize fleet size and storage capacity. A solution obtained in the declarative

model of the milk-run system under discussion allows to determine the routes for each

tugger train and the associated delivery times. In this context, the main contribution of

the present study is the identification of the relationship between takt time and the size

of replenishment batches, which allows to determine the delivery time windows for milkrun

delivery and, ultimately, the positioning of trade-off points. The results show that this

relationship is non-linear.

Improving production processes includes not only activities concerning manufacturing itself, but also all the activities that are necessary to achieve the main objectives. One such activity is transport, which, although a source of waste in terms of adding value to the product, is essential to the realization of the production process. Over the years, many methods have been developed to help manage supply and transport in such a way as to reduce it to the necessary minimum. In the paper, the problem of delivering components to a production area using trains and appropriately laid-out carriages was described. It is a milk run stop locations problem (MRSLP), whose proposed solution is based on the use of heuristic algorithms. Intelligent solutions are getting more and more popular in the industry because of the possible advantages they offer, especially those that include the possibility of finding an optimum local solution in a relatively short time and the prevention of human errors. In this paper, the applicability of three algorithms – tabu search, genetic algorithm, and simulated annealing – was explored.