Dynamic resource constrained multi-project scheduling problem with weighted earliness/tardiness costs

In this study, a conceptual framework is given for the dynamic multi-project scheduling problem with weighted earliness/tardiness costs (DRCMPSPWET) and a mathematical programming formulation of the problem is provided. In DRCMPSPWET, a project arrives on top of an existing project portfolio and a due date has to be quoted for the new project while minimizing the costs of schedule changes. The objective function consists of the weighted earliness tardiness costs of the activities of the existing projects in the current baseline schedule plus a term that increases linearly with the anticipated completion time of the new project. An iterated local search based approach is developed for large instances of this problem. In order to analyze the performance and behavior of the proposed method, a new multi-project data set is created by controlling the total number of activities, the due date tightness, the due date range, the number of resource types, and the completion time factor in an instance. A series of computational experiments are carried out to test the performance of the local search approach. Exact solutions are provided for the small instances. The results indicate that the local search heuristic performs well in terms of both solution quality and solution time

Operational Research IO2017, Valença, Portugal, June 28-30

This proceedings book presents selected contributions from the XVIII Congress of APDIO (the Portuguese Association of Operational Research) held in Valença on June 28–30, 2017. Prepared by leading Portuguese and international researchers in the field of operations research, it covers a wide range of complex real-world applications of operations research methods using recent theoretical techniques, in order to narrow the gap between academic research and practical applications. Of particular interest are the applications of, nonlinear and mixed-integer programming, data envelopment analysis, clustering techniques, hybrid heuristics, supply chain management, and lot sizing and job scheduling problems. In most chapters, the problems, methods and methodologies described are complemented by supporting figures, tables and algorithms. The XVIII Congress of APDIO marked the 18th installment of the regular biannual meetings of APDIO – the Portuguese Association of Operational Research. The meetings bring together researchers, scholars and practitioners, as well as MSc and PhD students, working in the field of operations research to present and discuss their latest works. The main theme of the latest meeting was Operational Research Pro Bono. Given the breadth of topics covered, the book offers a valuable resource for all researchers, students and practitioners interested in the latest trends in this field.info:eu-repo/semantics/publishedVersio

Reactive scheduling to treat disruptive events in the MRCPSP

Esta tesis se centra en diseñar y desarrollar una metodología para abordar el MRCPSP con diversas funciones objetivo y diferentes tipos de interrupciones. En esta tesis se exploran el MRCPSP con dos funciones objetivo, a saber: (1) minimizar la duración del proyecto y (2) maximizar el valor presente neto del proyecto. Luego, se tiene en cuenta dos tipos diferentes de interrupciones, (a) interrupción de duración, e (b) interrupción de recurso renovable. Para resolver el MRCPSP, en esta tesis se proponen tres estrategias metaheurísticas: (1) algoritmo memético para minimizar la duración del proyecto, (2) algoritmo adaptativo de forrajeo bacteriano para maximizar el valor presente neto del proyecto y (3) algoritmo de optimización multiobjetivo de forrajeo bacteriano (MBFO) para resolver el MRCPSP con eventos de interrupción. Para juzgar el rendimiento del algoritmo memético y de forrajeo bacteriano propuestos, se ha llevado a cabo un extenso análisis basado en diseño factorial y diseño Taguchi para controlar y optimizar los parámetros del algoritmo. Además se han puesto a prueba resolviendo las instancias de los conjuntos más importantes en la literatura: PSPLIB (10,12,14,16,18,20 y 30 actividades) y MMLIB (50 y 100 actividades). También se ha demostrado la superioridad de los algoritmos metaheurísticos propuestos sobre otros enfoques heurísticos y metaheurísticos del estado del arte. A partir de los estudios experimentales se ha ajustado la MBFO, utilizando un caso de estudio.DoctoradoDoctor en Ingeniería Industria

The job shop scheduling problem with convex costs

The job shop scheduling literature has been dominated by a focus on regular objective functions -- in particular the makespan -- in its half a century long history. The last twenty years have encountered a spike of interest in other objectives, such as the total weighted tardiness, but research on non-regular objective functions has always been isolated and scattered. Motivated by this observation, we present a tabu search heuristic for a large class of job shop scheduling problems, where the objective is non-regular in general and minimizes a sum of separable convex cost functions attached to the operation start times and the differences between the start times of arbitrary pairs of operations. This problem definition generalizes a number of problems considered earlier in the literature. A particular notion of "critical paths" derived from the so-called timing problem is at the core of the proposed neighborhood definition exploited successfully in a tabu search algorithm. The computational results attest to the promise of our work

A linear programming based method for the resource constrained multiproject scheduling problem with weighted earliness/tardiness costs

This study addresses the Resource Constrained Multi Project Scheduling Problem with Weighted Earliness Tardiness Costs (RCMPSPWET). In multi-project environments, the project portfolio of a company does often change dramatically in time. In this dynamic context, the arrival of a new project requires quoting a due date while keeping the disruptions to the existing plans and schedules to a minimum. The suggested solution method is an adaptation of the well known shifting bottleneck (SB) heuristic in the job shop literature. Initially, a base schedule is obtained by relaxing all resource capacities and solving the resulting model as a linear program (LP). The SB heuristic then resolves the resource conflicts present in the optimal solution of this resource relaxation iteratively by solving a set of single-resource weighted earliness tardiness scheduling subproblems with precedence constraints. The unit earliness and tardiness costs in the subproblems are estimated by drawing upon tools from LP sensitivity analysis recently proposed by Bülbül and Kaminsky [1] for a general job shop scheduling problem. The subproblems in the SB heuristic are a generalization of the NP-hard single machine weighted earliness tardiness problem, and a neighborhood search based algorithm is applied to these for the efficiency of the overall SB algorithm. The solution of a subproblem introduces new precedence relationships based on the concept of resource ows. These new precedence constraints are incorporated into the LP mentioned above and ensure that the capacity of the resource under consideration is observed. These steps are repeated until all resource conflicts are removed. The order in which the resource conflicts are resolved is a major determinant of the final solution quality, and therefore, a systematic tree search strategy is implemented for resolving the resource conflicts in different orders. A local search algorithm for the original problem is also adopted to benchmark the results

Modeling and optimizing the evacuation of hospitals based on the RCPSP with resource transfers

Partial or complete hospital evacuations might become necessary in various situations, e.g. due to a natural disaster such as a flood, due to an internal danger such as a fire, or, as it is frequently the case in Germany, due to the disposal of an aircraft bomb from World War II. In all of these situations, patients have to be evacuated from their locations inside the hospital to safety zones. Unlike in other evacuation problems where people can often help themselves to a certain degree, the same does not hold for this problem. In particular, many patients require assistance in order to reach the safety zones. Despite this additional challenge, only a limited amount of papers have been published that deal with the problem of evacuation planning for hospitals or other healthcare facilities. The problem of hospital evacuations is considered in this thesis in order to estimate the time required to evacuate all patients. In particular, the goal is to find a schedule minimizing the time required for the evacuation of all patients from their initial locations inside the hospital to safety zones inside or outside the hospital while taking into account the available assistants and aids as well as the infrastructure of the hospital. This problem is modeled as a multi-mode resource-constrained project scheduling problem with resource transfers and blockings as well as the makespan objective function. After the model has been presented, a first solution approach based on priority rules is proposed for this problem. For this approach, it is shown that an optimal solution may not always be contained in the considered solution space due to resource transfers of assistants and aids. As a result of this observation, the resource-constrained project scheduling problem with firstand second-tier resource transfers is considered and a solution approach is presented for this problem. For this, a solution representation based on resource flows as well as modifications based on this solution representation are introduced. Furthermore, some theoretical results related to the solution representation as well as the resulting neighborhoods have been developed. In particular, it is shown that for every project a resource flow exists that represents an optimal solution. Also, some results concerning the connectivity of the neighborhoods are presented. Afterward, a second solution approach for the problem of hospital evacuations is proposed in which solutions are represented as resource flows. Finally, computational results are reported for both, the solution approach for the resource-constrained project scheduling problem with first- and second-tier resource transfers as well as for the two solution approaches for the problem of hospital evacuations. For both of these problems, the results show that the solution approaches based on resource flows are able to obtain good solutions in a limited amount of time.Verschiedene Situationen können dazu führen, dass ein Krankenhaus ganz oder teilweise geräumt werden muss. Bei solchen Situationen kann es sich z.B. um eine Naturkatastrophe (z.B. eine Flut), um eine Gefahr innerhalb des Krankenhauses (z.B. ein Feuer) oder um die Entschärfung einer Fliegerbombe aus dem zweiten Weltkrieg handeln. In all diesen Situationen müssen Patienten aus den betroffenen Bereichen des Krankenhauses in sichere Zonen evakuiert werden. Im Gegensatz zu anderen Evakuierungsproblemen können sich Patienten dabei nicht immer aus eigener Kraft in Sicherheit bringen sondern sind auf Unterstützung angewiesen. Bisher wurde das Problem der Evakuierung von Krankenhäusern oder anderen Pflegeeinrichtungen in der Literatur jedoch kaum betrachtet. In dieser Arbeit wird das Problem der Evakuierung von Krankenhäusern mit dem Ziel betrachtet, die benötigte Zeit zur Evakuierung aller Patienten abzuschätzen. Insbesondere sollen Pläne generiert werden, welche die zur Evakuierung aller Patienten benötigte Zeit minimieren. Die Patienten müssen dabei mit Hilfe der verfügbaren Hilfsmittel und Hilfskräfte in Sicherheit gebracht werden. Weiterhin wird die Infrastruktur des Krankenhauses berücksichtigt. In dieser Arbeit wird dieses Problem als ein Mehrmodus ressourcenbeschränktes Projektplanungsproblem mit Ressourcentransfers und Blockierungen sowie der Zielfunktion, die maximale Bearbeitungsdauer zu minimieren, modelliert. Ein erster Lösungsansatz für dieses Problem basiert auf Prioritätsregeln. Für diesen Ansatz kann jedoch gezeigt werden, dass sich aufgrund der Ressourcentransfers nicht immer eine optimale Lösung im betrachteten Lösungsraum befindet. Aus diesem Grund wird das ressourcenbeschränkte Projektplanungsproblem mit Ressourcentransfers erster und zweiter Ordnung näher betrachtet und ein Lösungsansatz basierend auf Ressourcenflüssen für dieses Problem eingeführt. Dabei werden vor allem die Lösungsrepräsentation sowie Modifikationen von Ressourcenflüssen vorgestellt und theoretische Ergebnisse erarbeitet. Insbesondere wird gezeigt, dass für jedes Projekt ein Ressourcenfluss existiert, welcher eine optimale Lösung darstellt. Weiterhin werden einige Ergebnisse zum Zusammenhang der Nachbarschaften vorgestellt. Danach wird ein zweiter Lösungsansatz basierend auf Ressourcenflüssen für das Problem der Evakuierung von Krankenhäusern eingeführt. Abschließend werden Rechenergebnisse für die verschiedenen Lösungsansätze angegeben, welche für das Problem der Evakuierung von Krankenhäusern sowie für das ressourcenbeschränkte Projektplanungsproblem mit Ressourcentransfers erster und zweiter Ordnung entwickelt wurden. Dabei ergibt sich, dass Lösungsansätze basierend auf Ressourcenflüssen in der Lage sind, innerhalb kurzer Zeit gute Ergebnisse zu erzielen

RESOURCE PLANNING WITH EMBEDDED JUST-IN-TIME CHARACTERISTICS FOR MAKE-TO-ORDER DISCRETE PRODUCTION SYSTEMS

Adopting a make-to-order (MTO) production mode allows manufacturers to accommodate a wider variety of customer requirements without a prohibitive increase in inventory of finished products. Since MTO production involves a wide variety of process features, a resource plan is necessary to coordinate production of customer orders so that resources are used efficiently and customer order due dates are met.This dissertation develops optimal and heuristic methods that embed characteristics of the just-in-time (JIT) philosophy to create resource plans for MTO environments. JIT is a well-known productivity concept in which jobs are attempted to be started near to and finished on their due dates in order to reduce work in process (WIP), inventory, lead time, and cost. In the JIT philosophy, an ideal plan for a single order would have zero queue time, zero earliness, and zero lateness. The methods remain cognizant of the ideal plan for an order as they make adjustments to the actual plan for each order that are necessary to accommodate resource constraints.A new binary integer linear programming (BILP) model is formulated to solve resource planning problems in MTO environments. The objective function contains weighted costs for earliness, tardiness, lead time, and subcontractor capacity. The initial solution is generated using the ideal plan for each order. Extensive computational results show that this initialization method often reduces computational time such that the BILP model can reach the optimal solution within an acceptable amount of time when it otherwise could not.Due to the extremely limited scalability of optimal methods, which renders them inappropriate for most realistic make-to-order environments, a heuristic method utilizing tabu search is developed to solve resource planning problems. This is a two-phase algorithm. Like the optimal method, the tabu search algorithm in the first phase also generates an initial solution using the ideal plan for each order, and it then creates a finite capacity plan. It furthermore remains cognizant of the ideal plan in the second phase as it searches for solutions that respect resource constraints but that have good performance in terms of order earliness, tardiness, and lead time. A benchmark study of the developed algorithm reveals that the tabu search algorithm provides better solutions in terms of problem scalability and solution quality than other methods including the BILP optimization approach and other heuristic approaches such as FIFO or EDD

A dynamic scheduling model for construction enterprises

The vast majority of researches in the scheduling context focused on finding optimal or near-optimal predictive schedules under different scheduling problem characteristics. In the construction industry, predictive schedules are often produced in advance in order to direct construction operations and to support other planning activities. However, construction projects operate in dynamic environments subject to various real-time events, which usually disrupt the predictive optimal schedules, leading to schedules neither feasible nor optimal. Accordingly, the development of a dynamic scheduling model which can accommodate these real-time events would be of great importance for the successful implementation of construction scheduling systems. This research sought to develop a dynamic scheduling based solution which can be practically used for real time analysis and scheduling of construction projects, in addition to resources optimization for construction enterprises. The literature reviews for scheduling, dynamic scheduling, and optimization showed that despite the numerous researches presented and application performed in the dynamic scheduling field within manufacturing and other industries, there was dearth in dynamic scheduling literature in relation to the construction industry. The research followed two main interacting research paths, a path related to the development of the practical solution, and another path related to the core model development. The aim of the first path (or the proposed practical solution path) was to develop a computer-based dynamic scheduling framework which can be used in practical applications within the construction industry. Following the scheduling literature review, the construction project management community s opinions about the problem under study and the user requirements for the proposed solution were collected from 364 construction project management practitioners from 52 countries via a questionnaire survey and were used to form the basis for the functional specifications of a dynamic scheduling framework. The framework was in the form of a software tool fully integrated with current planning/scheduling practices with all core modelling which can support the integration of the dynamic scheduling processes to the current planning/scheduling process with minimal experience requirement from users about optimization. The second research path, or the dynamic scheduling core model development path, started with the development of a mathematical model based on the scheduling models in literature, with several extensions according to the practical considerations related to the construction industry, as investigated in the questionnaire survey. Scheduling problems are complex from operational research perspective; so, for the proposed solution to be functional in optimizing construction schedules, an optimization algorithm was developed to suit the problem's characteristics and to be used as part of the dynamic scheduling model's core. The developed algorithm contained few contributions to the scheduling context (such as schedule justification heuristics, and rectification to schedule generation schemes), as well as suggested modifications to the formulation and process of the adopted optimization technique (particle swarm optimization) leading to considerable improvement to this techniques outputs with respect to schedules quality. After the completion of the model development path, the first research path was concluded by combining the gathered solution's functional specifications and the developed dynamic scheduling model into a software tool, which was developed to verify & validate the proposed model s functionalities and the overall solution s practicality and scalability. The verification process started with an extensive testing of the model s static functionality using several well recognized scheduling problem sets available in literature, and the results showed that the developed algorithm can be ranked as one of the best state-of-the-art algorithms for solving resource-constrained project scheduling problems. To verify the software tool and the dynamic features of the developed model (or the formulation of data transfers from one optimization stage to the next), a case study was implemented on a construction entity in the Arabian Gulf area, having a mega project under construction, with all aspects to resemble an enterprise structure. The case study results showed that the proposed solution reasonably performed under large scale practical application (where all optimization targets were met in reasonable time) for all designed schedule preparation processes (baseline, progress updates, look-ahead schedules, and what-if schedules). Finally, to confirm and validate the effectiveness and practicality of the proposed solution, the solution's framework and the verification results were presented to field experts, and their opinions were collected through validation forms. The feedbacks received were very positive, where field experts/practitioners confirmed that the proposed solution achieved the main functionalities as designed in the solution s framework, and performed efficiently under the complexity of the applied case study

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes