Solution approaches for facility location of medical supplies for large-scale emergencies
Computers and Industrial Engineering
Dynamic supply chain design with inventory
Computers and Operations Research
Computers and Electronics in Agriculture
Resource assignment and scheduling based on a two-phase metaheuristic for cropping system
Computers and Electronics in Agriculture
Mathematical modeling and solving procedure of the planar storage location assignment problem
Computers and Industrial Engineering
Computers and Operations Research
Capacitated facility location problem with general setup cost
Computers and Operations Research
Computers and Electronics in Agriculture
Computers and Industrial Engineering
Robotics and Computer-Integrated Manufacturing
Facility location problems: A parameterized view
Discrete Applied Mathematics
Survey: Covering problems in facility location: A review
Computers and Industrial Engineering
Computers and Electronics in Agriculture
Location allocation modeling for healthcare facility planning in Malaysia
Computers and Industrial Engineering
Facility location and scale decision problem with customer preference
Computers and Industrial Engineering
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In this paper, we address the problem of the location of sugar cane loading stations in Thailand. A loading station is a facility for collecting cane from small farmers; the cane is then transported to a sugar mill by a large truck. An improperly located loading station can result in high investment and transportation costs in the sugar industry. A mathematical model and a heuristic algorithm were developed to determine the suitable capacity of existing loading stations, the locations and capacities of new loading stations and the allocations of cane field harvests to each loading station. The model accounted for variations in the cane yield of each field during the harvesting periods and between crop years. The objective function was the minimization of the associated costs, including the investment costs, the transportation costs and the cost of the cane yield loss if the cane is not harvested at an optimal time. The performance of the developed heuristics was assessed under various scenarios. The results were shown to deviate slightly from the solution to the mathematical model. The sensitivities of the solutions under variations of the transportation cost, yield loss cost and investment costs were studied. The model was also applied to an industrial case study. A relevant and accurate solution was obtained.