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Towards an evolutionary guided exact solution to elective surgery scheduling under uncertainty and ward restrictions

机译:走向一种进化指导的精确解决方案,以在不确定性和病区限制下选修手术调度

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The problem of constructing surgery schedules, with limited downstream ward capacity, is formulated as a mathematical model with probabilistic constraints. This exact model becomes computationally intractable for mathematical programming solvers as the number of patients increase. An evolutionary algorithm is used to restrict the size of the search space, making the problem tractable again, effectively guiding the solvers towards an exact and feasible solution. Solutions are validated using Monte Carlo simulations during the evolutionary search. The optimization problem is inspired by real challenges faced by many hospitals today and tested on real-life hospital data.
机译:构建手术时间表的问题,下游病房容量有限,配制为具有概率约束的数学模型。随着患者的数量增加,这种确切的模型对于数学编程求解器而言变得棘手。一种进化算法用于限制搜索空间的大小,再次使问题变得令人作用,有效地引导求解器朝向精确可行的解决方案。在进化搜索期间使用Monte Carlo模拟验证解决方案。优化问题受到今天许多医院面临的真正挑战的启发,并在现实生活医院数据上测试。

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