Abstract
The collection, transport, and final disposal of hospital waste may cause contamination and disease if improperly handled. Therefore, such residues are hazardous to the health of waste collectors. These wastes are generated by public agencies, such as hospitals, family health centers, dialysis centers, and private healthcare providers. In this study, a mixed-integer linear programming model is proposed for monthly customer scheduling and route assignment. The proposed approach was fulfilled according to customers’ collection frequency, truck capacity, and customer geographical location. The proposed mathematical model successfully balanced the number of customers and the workload during each day. The effectiveness of the proposed model was tested on data obtained from a waste collection company. The model has been implemented in AMPL language, and the performance of commercial solvers, GUROBI and CPLEX, to obtain an optimal solution were tested. The results show the efficiency of the proposed approach to balance the workload concerning previous scheduling is done ad hoc at the company. The use of the formulated model provides an automatic procedure that was previously performed manually. The methodology can be adapted to other companies with similar requirements.
Highlights
Because of difficulties or limitations in assigning resources, including machines, facilities, staff, or inputs, one of the leading problems facing any company’s operations management, whether in manufacturing or services, is customer-proposed scheduling work activities
This paper proposes a mathematical model for hazardous infectious waste collection and government aid distribution to control COVID-19
We have introduced the problem of scheduling and assignment of customers in Hospital Waste Collection Routes
Summary
Because of difficulties or limitations in assigning resources, including machines, facilities, staff, or inputs, one of the leading problems facing any company’s operations management, whether in manufacturing or services, is customer-proposed scheduling work activities. Such problems are difficult to solve and have been the subject of several research studies. Many experts have proposed solutions, ranging from heuristics and metaheuristics approaches to the application of precisely defined rules. Both manual techniques and specialized software programs have been employed by Ballesteros Silva and Duque Vanegas [1]. The classical models in the literature overlook such issues as described by De la Peña et al [2]
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