Abstract
The tea picking schedule at PT Perkebunan Ciater is set to be the same for all plantation blocks. In fact, the altitude from sea level and the pruning age of each plantation block is different, this results in the difference of buds’ growth. The implementation of the same picking schedule causes the quality and quantity of tea buds often could not be fulfilled. This research is to determine the precise picking schedule by considering the buds’ growth of each plantation block. Two steps are implemented to solve the problem. The first step is to look for picking period and the pattern of buds’ quality for each plantation block, which corresponds to the altitude of the location and the pruning age. The regression method is applied in this first step. The buds’ quality pattern is then used to determine the cost of decreasing buds’ quality and the costs of the buds that left in the plantation. The second step is to develop the picking schedule using dynamic programming, which minimizes the total cost of picking. In addition to this, we also develop a rolling schedule, which schedule time interval is three days. The model results show that the proposed schedule gives a better total cost than the current schedule and the buds’ quality target is easier to achieve.
Highlights
Quality is one of the key competitions in marketing of a product
The tea picking schedule at PT Perkebunan Ciater is set to be same for all plantation blocks, that is every 12-14 days
Some authors considered the uses of dynamic programming too, that is [19] proposed a dynamic programming algorithm for the knapsack problem with setup that common in production planning applications, [20] developed two dynamic programming algorithms where the first algorithm was proposed for linear complexity on the number of items, while the latter was used for linear complexity at the knapsack capacity
Summary
Quality is one of the key competitions in marketing of a product. Tea is one of the products that relies on quality as the key competition in its marketing. [5] proposed an exact algorithm based on dynamic programming to find optimal sequences for the job-shop scheduling problem. [6] developed a stochastic dynamic programming model to optimize aircraft replacement scheduling by taking into consideration the fluctuations in the market demand and the status of the aircraft. [7] developed approximate dynamic programming (ADP) algorithms to solve stochastic project scheduling problems. [9] proposed a new dynamic programming algorithm for solving scheduling problem of independent tasks with common due date and to minimize the total weighted tardiness. [25] proposed a markovian decision model and ADP to solve vehicle routing problem for emissions minimization, whereas [26] combined a genetic algorithm and exact dynamic programming procedure for green vehicle routing and scheduling problem. : the labour wage of each kg of tea buds at plantation block i, based on the picking capacity and buds’ analysis results zi : the weight of tea buds picked at the plantation block i
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