Abstract

In Thailand, the harvesting season for sugarcane usually begins in November and ends the following May. At the beginning of each harvesting season, the Royal Thai government sets the price of two types of sugarcane, namely fresh and fired, based on sweetness (sugar content) and gross weight of sugarcane delivered to the sugar factories. The aim of the present research is to determine optimal harvesting policies for the two types of sugarcane in sugarcane producing regions of Thailand in order to maximize revenue and minimize harvesting cost. In this paper, a harvesting policy is defined as the amount of each type of sugarcane harvested and delivered to the sugar factories during each 15-day period of a harvesting season. Two optimization methods have been used to solve this optimization problem, namely the ε-constraints method and a quasi-Newton optimization method. In the ε-constraints method, the problem is considered as a bi-objective optimization problem with the main objective being to determine harvesting policies that maximize the total revenue subject to upper bounds on the harvesting cost. In the quasi-Newton method, the aim is to determine the harvesting policy which gives maximum profit to the farmers subject to constraints on the maximum amount that can be cut in a 15-day period. The methods are used to determine optimal harvesting policies for the north, central, east, and north-east regions of Thailand for harvesting seasons 2012/13, 2013/14, and 2014/15 based on the data obtained from the Ministry of Industry and the Ministry of Agriculture and Co-operatives of the Royal Thai government.

Highlights

  • The sugarcane industry is one of the major agro-industries in Thailand; it is important to the Thai economy because sugar is one of the top five agricultural products that the country exports

  • Region, and year, we have examined the effect of changing the values of the upper bound on the maximum cutting per period umax and the effect of reducing the maintenance costs by a factor mcf (0 ≤ mcf ≤ 1) of the actual maintenance cost

  • 7 Results 7.1 Bi-objective optimization In the bi-objective optimization, we assumed that it was possible to cut all of the sugarcane in one 15-day period

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Summary

Introduction

The sugarcane industry is one of the major agro-industries in Thailand; it is important to the Thai economy because sugar is one of the top five agricultural products that the country exports. It helps create income of approximately 180 billion baht a year [1]. Sugarcane is grown in the north, central, east, and north-east regions of Thailand. In 2013/14, the north-east region produced 45 million tonnes of the total of 103.5 million tonnes of Pornprakun et al Advances in Difference Equations (2019) 2019:257 sugarcane produced in the country, the north, central, and east regions producing 24, 30, and 4.5 million tonnes, respectively

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