Optimal fuzzy scheduling and sequencing of multiple-period operating room

Abstract

Little research has considered fuzzy scheduling and sequencing problem in operating rooms. Multiple-period fuzzy scheduling and sequencing of patients in operating rooms optimization models are proposed in this research taking into consideration patient‘s preference. The objective of the scheduling optimization model is obtaining minimal undertime and overtime and maximum patients' satisfaction about the assigned date. The objective of sequencing the optimization model is both to minimize overtime and to maximize patients' satisfaction about the assigned time. A real-life case study from a hospital that offers comprehensive surgical procedures for all surgical specialties is considered for illustration. Research results showed that the proposed models efficiently scheduled and sequenced patients while considering their preferences and hospitals operating costs. In conclusion, the proposed optimization models may result in improving patient satisfaction, utilizing hospital's resources efficiently, and providing assistance to decision makers and planners in solving effectively fuzzy scheduling and sequencing problems of operating rooms.

A new model for operating room scheduling with elective patient strategy

“…Riise et al (2016) presented an ORS model with three-time horizons (daily, weekly, and real-time) and the objective of minimizing surgery time for a hospital in Norway. Al-Refaie et al (2018a) developed multiple-period fuzzy scheduling considering patients' preferences and objectives of minimizing overtime and maximizing patients' satisfaction. Belkhamsa et al (2018) studied ORS with resource constraints in pre-operative, intraoperative, and postoperative stages and availability of material resources, specialties, and human resources.…”

Multi-objective integrated planning and scheduling model for operating rooms under uncertainty

“…Various methods such as robust optimization, stochastic programming, and fuzzy approach have been utilized to deal with uncertainty in operating room planning and scheduling problems. Al-Refaie et al 28 addressed a scheduling and sequencing problem for a multiple period operating room model. They developed some models by considering the preferences of patients to deal with the uncertainty in their problem.…”

Developing a new hybrid soft computing technique in predicting ultimate pile bearing capacity using cone penetration test data

“…In addition, CPT is a commonly used soil exploration survey in engineering applications because it is quick, economic, and could continuously obtain physical soil parameters (Eslami, 1997; Abu-Farsakh and Titi, 2004). In recent years, some researchers developed concepts of advanced artificial intelligence (AI) in different engineering applications, such as engineering mechanics, design of energy-saving buildings, automation, and construction (Coello and Aguirre, 2002; Nariman-Zadeh et al ., 2003; Hanna, 2007; Padmini et al ., 2008; Rossi and Lanzetta, 2013; Hu et al ., 2014; Zeng et al ., 2014; Kontovourkis et al ., 2015; Salido et al ., 2015; Adeniran and El-Ferik, 2017; Persson and Ölvander, 2017; Thimmisetty et al ., 2017; Al-Refaie et al ., 2018; Keles, 2018; Lin and Huang, 2018; Mirabi and Seddighi, 2018; Zimmermann et al ., 2018). In recent years, applications of AI models have become widespread through civil engineering projects (e.g., Armaghani et al ., 2017, 2018; Koopialipoor et al ., 2018).…”