Álvaro García-Sánchez

Combining Simulation and Tabu Search for Oil-derivatives Pipeline Scheduling

In this chapter a methodology for addressing a real-world multicommodity pipeline scheduling problem is presented. For this problem, a Tabu Search and a Simulation model have been devised. The simulation model allows an accurate and suitable assessment of every particular schedule, whereas the Tabu Search guides the searching process and eventually succeeds in obtaining satisfactory schedules in terms of a set of relevant criteria. This methodology has been applied to a particular subsystem of the pipeline Spanish network. As a result, the proposed Tabu Search has proved to be an effective and efficient technique for solving the problem.

Managing daily surgery schedules in a teaching hospital: a mixed-integer optimization approach

BackgroundThis study examined the daily surgical scheduling problem in a teaching hospital. This problem relates to the use of multiple operating rooms and different types of surgeons in a typical surgical day with deterministic operation durations (preincision, incision, and postincision times). Teaching hospitals play a key role in the health-care system; however, existing models assume that the duration of surgery is independent of the surgeon’s skills. This problem has not been properly addressed in other studies. We analyze the case of a Spanish public hospital, in which continuous pressures and budgeting reductions entail the more efficient use of resources.MethodsTo obtain an optimal solution for this problem, we developed a mixed-integer programming model and user-friendly interface that facilitate the scheduling of planned operations for the following surgical day. We also implemented a simulation model to assist the evaluation of different dispatching policies for surgeries and surgeons. The typical aspects we took into account were the type of surgeon, potential overtime, idling time of surgeons, and the use of operating rooms.ResultsIt is necessary to consider the expertise of a given surgeon when formulating a schedule: such skill can decrease the probability of delays that could affect subsequent surgeries or cause cancellation of the final surgery. We obtained optimal solutions for a set of given instances, which we obtained through surgical information related to acceptable times collected from a Spanish public hospital.ConclusionsWe developed a computer-aided framework with a user-friendly interface for use by a surgical manager that presents a 3-D simulation of the problem. Additionally, we obtained an efficient formulation for this complex problem. However, the spread of this kind of operation research in Spanish public health hospitals will take a long time since there is a lack of knowledge of the beneficial techniques and possibilities that operational research can offer for the health-care system.

Mixed integer programming model for optimizing the layout of an ICU vehicle

BackgroundThis paper presents a Mixed Integer Programming (MIP) model for designing the layout of the Intensive Care Units (ICUs) patient care space. In particular, this MIP model was developed for optimizing the layout for materials to be used in interventions. This work was developed within the framework of a joint project between the Madrid Technical Unverstity and the Medical Emergency Services of the Madrid Regional Government (SUMMA 112).MethodsThe first task was to identify the relevant information to define the characteristics of the new vehicles and, in particular, to obtain a satisfactory interior layout to locate all the necessary materials. This information was gathered from health workers related to ICUs. With that information an optimization model was developed in order to obtain a solution. From the MIP model, a first solution was obtained, consisting of a grid to locate the different materials needed for the ICUs. The outcome from the MIP model was discussed with health workers to tune the solution, and after slightly altering that solution to meet some requirements that had not been included in the mathematical model, the eventual solution was approved by the persons responsible for specifying the characteristics of the new vehicles. According to the opinion stated by the SUMMA 112s medical group responsible for improving the ambulances (the so-called coaching group), the outcome was highly satisfactory. Indeed, the final design served as a basis to draw up the requirements of a public tender.ResultsAs a result from solving the Optimization model, a grid was obtained to locate the different necessary materials for the ICUs. This grid had to be slightly altered to meet some requirements that had not been included in the mathematical model. The results were discussed with the persons responsible for specifying the characteristics of the new vehicles.ConclusionThe outcome was highly satisfactory. Indeed, the final design served as a basis to draw up the requirements of a public tender. The authors advocate this approach to address similar problems within the field of Health Services to improve the efficiency and the effectiveness of the processes involved. Problems such as those in operation rooms or emergency rooms, where the availability of a large amount of material is critical are eligible to be dealt with in a simmilar manner.

Parallel CUDA Architecture for Solving de VRP with ACO

Ant Colony Optimization (ACO) is an effective meta-heuristic for the solution of a wide variety of problems. Its computation is intrinsically massively parallel, and it is therefore theoretically well-suited for implementation on Graphics Processing Units (GPUs). In this paper, we propose a parallelization strategy to solve the VRP with ACO on the GPU.

A conceptual model for integrating strategic supply management into the supply chain

In this paper, a strategic supply management reference model for supplier integration in the supply chain is presented. The model developed is based on the comparative case study of two relevant industries – automotive and aircraft – and may be suitable for other industries. The survey and the subsequent analysis of these industries have confirmed the strategic importance of supplies and the need for an integrated approach of supply management, both in terms of internal processes and of external suppliers. Additionally, the study has proved that there is not a unique model for supply management, valid for all industries.

A MILP Event Based Formulation for a Real-world Multimode RCSP with Generalized Temporal Constraints

Scheduling is becoming much more important in every industry. However, the standard RCSP usually does not cover all the characteristics of real world problems. In this work, we present an Event Based MILP formulation for a Multimode Resource Constraint Scheduling Problem of direct application for some industries, as aeronautical assembly lines. Taking as a starting point one of the last MILP formulations for standard RCSP, our contribution is to provide a formulation which covers the multimode case and more general temporal constraints than the ones usually referred to in the literature.

Scatter Search for locating a treatment plant and the necessary transfer centers in a reverse network

In the area of Reverse Logistics, the problem of selecting locations for its key facilities consists in locating waste treatment plants, transfer centers and, in general, collection facilities. In this paper a location problem in a reverse system is presented (the so-called STPNTCLP). Put simply, this problem consists in deciding where to locate one treatment plant and its necessary transfer centers. The problem both in deterministic and stochastic terms is solved with a Scatter Search based approach that offers a better performance in both real and randomly generated cases than the proposed exact method (MILP formulation).

Flexible Job Shop Scheduling With Operators in Aeronautical Manufacturing: A Case Study

This paper analyzes a flexible job shop scheduling problem with operators and is motivated by a real-life case study of the aeronautical industry, where each process can be performed on alternative machines (shared by multiple products) and requires not only machines but also some operators to execute the process. One goal of this scheduling is to minimize the number of operators and airframes that are needed in the assembly line. Minimizing the number of airframes in the assembly line, which is particularly important due to the cost of each airframe, is generally ignored in production planning models that are used in prior studies. Moreover, the output of the program refers to a set of schedules that includes different combinations of number of operators and intermediate stock, to enable a better decision making. A mixed integer linear programming model is presented to solve this problem. Experimentation was conducted using real-life examples from the aeronautical industry. The solutions that are presented in this paper outperformed current industrial methods in both quality and calculation time. To the best of our knowledge, this variant has not been addressed in prior studies either in scheduling or in aeronautics contexts. However, minimizing the number of operators and intermediate stock could have significant implications for numerous labor intensive industries, contributing to enhanced and more agile decision making processes.

Analysis of the Robustness of Production Scheduling in Aeronautical Manufacturing Using Simulation: A Case Study

The use of PLM tools is widely spread in the aeronautical industry. Although scheduling and line balancing have remained aside these tools for long, they are being developed in the recent years. They need to tackle with complex resource constrained scheduling problems. In this work we present a simulation model we have developed for evaluating the robustness of a baseline scheduling for an aero structure assembly line. To begin with, we have identified and quantified the main causes of the disruptions. Then we have created a discrete event simulation model of the production line to take everything into consideration, and then run several experiments to evaluate different production planning obtained with the different methodologies and the impact of failures in the deliveries of finished products. Also, different scenarios in terms of failure quantity and typology have been studied.

The Role of Complexity and Flexibility of the Instance in the Joint Solution Approach

Many pieces of research address the development of new algorithms and new solution techniques for decision-making; however, most of them do not consider the characteristics of instance in their analysis, such as the complexity and flexibility of the instance. Building a complex model, such as a joint model, requires a huge amount of time and effort while the resulting solution of such joint models may or may not be the best solution for all the actors involved in the process. Therefore, it is important to make an in-depth analysis of the instance before investing the time and effort to build a joint model. In this regard, this paper provides an instance evaluation procedure to help decision-makers decide whether to use joint decision or not for a particular instance.