Malek Masmoudi

Project scheduling under uncertainty using fuzzy modelling and solving techniques

In the real world, projects are subject to numerous uncertainties at different levels of planning. Fuzzy project scheduling is one of the approaches that deal with uncertainties in project scheduling problem. In this paper, we provide a new technique that keeps uncertainty at all steps of the modelling and solving procedure by considering a fuzzy modelling of the workload inspired from the fuzzy/possibilistic approach. Based on this modelling, two project scheduling techniques, Resource Constrained Scheduling and Resource Leveling, are considered and generalized to handle fuzzy parameters. We refer to these problems as the Fuzzy Resource Constrained Project Scheduling Problem (FRCPSP) and the Fuzzy Resource Leveling Problem (FRLP). A Greedy Algorithm and a Genetic Algorithm are provided to solve FRCPSP and FRLP respectively, and are applied to civil helicopter maintenance within the framework of a French industrial project called Helimaintenance.

Fuzzy tactical project planning: Application to helicopter maintenance

Inspired by a helicopter maintenance planning problem, we study the integration of uncertainties into tactical multi-resource, multi-project planning (Rough Cut Capacity Planning). We model uncertainty by a fuzzy/possibilistic approach instead of a stochastic approach to be able to develop robust plans in situations where very limited data is available. We refer to the problem as the Fuzzy Rough Cut Capacity Problem (FR-CCP). We propose an adaptation of periodic workload to fuzziness, and develop a simulated annealing meta-heuristic to solve the capacity planning problem. We apply this method to the helicopter maintenance activity within the frame of a French industrial project called He´limaintenance1.

A GA-based fuzzy resource leveling optimization for helicopter maintenance activity

Genetic algorithm is one of the main heuristics that have been applied to scheduling problems in the last few decades. This paper presents a generalization of the genetic algorithm for solving project scheduling problem under time uncertainties within resource leveling technique. The generalization consists of handling fuzzy time parameter and fuzzy resource distribution instead of crisp ones. The provided fuzzy genetic algorithm is justified and applied to a real multi-project and multi-resources problem from the helicopter maintenance activity.

General variable neighborhood search for home healthcare routing and scheduling problem with time windows and synchronized visits

Abstract Home healthcare centers are facing increasing demands and researchers are attracted by the related routing and scheduling issue that is presented in literature as a VRP with synchronization and time windows constraints. The goal is to optimize the assignment of visits to home caregivers and the sequence of visits execution. In this paper, a General Variable Neighborhood Search is provided. Experiments conducted on benchmark instances from the literature clearly show that our method is fast and outperforms the existing approaches on half of the instances.

Decision Support Procedure for Medical Equipment Maintenance Management

Hospitals outsource several activities of the service support in order to focus on the core healthcare production as maintenance service. Recently, faced to the sophistication and the costs of medical equipment that continue to escalate, governments have implemented new reforms to control costs and improve the efficiency and the quality. Hospitals become interested in minimizing the total operational cost, by optimizing healthcare production planning and their support activities. Reorganizing the medical equipment maintenance service becomes a priority for the hospital managers to reduce the cost and the dependency on external parties while ensuring that the medical devices are safe, accurate, and operating at the required level of performance. In this article, we propose an efficient procedure to take the appropriate decisions for medical equipment maintenance such as the selection of maintenance strategy, the insourcing/outsourcing, and the selection of contracts’ type and content. A practical application of this procedure in the Tunisian context is considered. Nevertheless, our procedure is general and can be tailored to hospitals in both developed and developing countries.

Fuzzy uncertainty modelling for project planning: application to helicopter maintenance

Maintenance is an activity of growing interest, especially for critical systems. In particular, aircraft maintenance costs are becoming an important issue in the aeronautical industry. Managing an aircraft maintenance centre is a complex activity. One of the difficulties comes from the numerous uncertainties that affect the activity and disturb the plans in the short and medium term. Based on a helicopter maintenance planning and scheduling problem, we study in this paper the integration of uncertainties into tactical and operational multi-resource, multi-project planning (respectively Rough Cut Capacity Planning and the Resource Constraint Project Scheduling Problem). Our main contributions are in modelling the periodic workload on a tactical level considering uncertainties in macro-task work content, and modelling the continuous workload on the operational level considering uncertainties in task duration. We model uncertainties using a fuzzy/possibilistic approach instead of a stochastic approach since very limited data are available. We refer to the problems as the Fuzzy Rough Cut Capacity Problem (FRCCP) and the Fuzzy Resource Constraint Project Scheduling Problem (RCPSP). We apply our models to helicopter maintenance activity within the frame of the Helimaintenance project, an industrial project approved by the French Aerospace Valley cluster that aims at building a centre for civil helicopter maintenance.

A New PSO-based Algorithm for Two-Dimensional Non-Guillotine Non-Oriented Cutting Stock Problem

ABSTRACT In this paper, a new algorithm is proposed for the two-dimensional non-guillotine non-oriented cutting stock problem. The considered problem consists of cutting small rectangular pieces of predetermined sizes from large but finite rectangular plates. The objective is to generate cutting patterns that minimize the unused area and fulfill customer orders. The proposed algorithm is a combination of a new particle swarm optimization approach with a heuristic criterion inspired from the literature. The algorithm is tested on twenty-two instances divided into two sets. Corresponding results show the algorithm efficiency in optimizing the trim loss that is comprised between 2.6% and 7.8% for all considered instances.

Multicriteria decision making for Medical equipment maintenance: Insourcing, outsourcing and service contract

Hospitals outsource several activities of support in order to focus on healthcare production. Maintenance is one of these support activities. Recently, faced with rising healthcare costs, governments have implemented new reforms to control costs and improve efficiency and quality. Hospitals became interested in minimizing the total cost of the activity, by minimizing both healthcare production activities and support activities. In developing countries, medical equipment maintenance is costly and partially mastered most of the time because it is usually managed by external service contracts [1]. Reorganizing medical equipment maintenance service became a priority for hospital managers to reduce the cost and dependency while raising quality and reliability. In this paper, we propose an efficient procedure to take the appropriate decisions for medical equipment maintenance such as the strategy, to insource or outsource and the type of contract in case of outsourcing and its content.

Graph coloring approach with new upper bounds for the chromatic number: Team building application

In this paper, we focus on the coloration approach and estimation of chromatic number. First, we propose an upper bound of the chromatic number based on the orientation algorithm described in previous studies. This upper bound is further improved by developing a novel coloration algorithm. Second, we make a theoretical and empirical comparison of our bounds with Brooks’s bound and Reed’s conjecture for class of triangle-free graphs. Third, we propose an adaptation of our algorithm to deal with the team building problem respecting several hard and soft constraints. Finally, a real case study from healthcare domain is considered for illustration.

Two metaheuristics for solving no-wait operating room surgery scheduling problem under various resource constraints

Abstract The problem studied in this paper is operating room surgery scheduling, with resource constraints in each of the three following stages: preoperative, intraoperative, and postoperative stages. The availability of material resources, specialties and qualifications of human resources are integrated, and the aim is to schedule surgeries while minimizing the maximum end time of last activity in stage 3 and the total idle time in the operating rooms. Two metaheuristics, an iterative local search approach and a hybrid genetic algorithm, are provided and tested on real workday instances from the literature. Computational experiments showed that our metaheuristics outperformed the current state-of-the-art solving algorithm which is an ant colony optimization. The hybrid genetic algorithm reached small superiority vs. the iterative local search algorithm. The average reduction in the end time (the total idle time) was 24% (59%) with the iterated local search approach and 24% (70%) with the hybrid genetic algorithm vs. 14% (55%) with the ant colony optimization algorithm.