No abstract

We study the stochastic resourceconstrained project scheduling problem or SRCPSP, where project activities have stochastic durations. A solution is a scheduling policy, and we propose a new class of policies that is a generalization of most of the classes described in the literature. A policy in this new class makes a number of a-priori decisions in a preprocessing phase while the remaining scheduling decisions are made online. A two-phase local search algorithm is proposed to optimize within the class. Our computational results show that the algorithm has been efficiently tuned towards finding high-quality solutions, and that it outperforms all existing algorithms for large instances. The results also indicate that the optimality gap even within the larger class of elementary policies is very small.

No abstract

In this paper we propose a heuristic approach that computes the order in which patients will be treated in an ambulatory chemotherapy center. Each patient follows an individual treatment plan that fixes dates for series of drug injections separated by recovery periods. The daily care process has three steps: consultation with the oncologist, drug preparation in the pharmacy and drug injection in medical beds. The facility closes after the last injection. As drug injection varying considerably in duration -from 15 minutes to 6 hours -bad schedules lead to excessive overtime. In addition, after the consultation the oncologist may decide to cancel the injection because of a weak patient's health condition. In the current setting of the chemotherapy facility we work with, First Come First Served policy controls the care process. In this study, we propose to compute a common priority list of patients for consultation and injection phases. A unique list of patients is a simple tool used by nurses to manage the flow of patients and to react to uncertain events. A GRASP algorithm is developed to compute optimized list of patients in few seconds as the operating planning context requires. Two objectives are considered; the closing time and the overworking time of the facility. Numerical experiments show that our GRASP is able to quickly reach near optimal solutions and that list of patients policy performance is comparable to more complex scheduling policies. Benchmark data sets are built based on historical data of the French chemotherapy facility, ICL in Saint-Étienne.