Efficient Heuristic Algorithms for Single-Vehicle Task Planning With Precedence Constraints

This article investigates the task planning problem where one vehicle needs to visit a set of target locations while respecting the precedence constraints that specify the sequence orders to visit the targets. The objective is to minimize the vehicle’s total travel distance to visit all the targets while satisfying all the precedence constraints. We show that the optimization problem is NP-hard, and consequently, to measure the proximity of a suboptimal solution from the optimal, a lower bound on the optimal solution is constructed based on the graph theory. Then, inspired by the existing topological sorting techniques, a new topological sorting strategy is proposed; in addition, facilitated by the sorting, we propose several heuristic algorithms to solve the task planning problem. The numerical experiments show that the designed algorithms can quickly lead to satisfying solutions and have better performance in comparison with popular genetic algorithms

Efficient Routing for Precedence-Constrained Package Delivery for Heterogeneous Vehicles

This paper studies the precedence-constrained task assignment problem for a team of heterogeneous vehicles to deliver packages to a set of dispersed customers subject to precedence constraints that specify which customers need to be visited before which other customers. A truck and a micro drone with complementary capabilities are employed where the truck is restricted to travel in a street network and the micro drone, restricted by its loading capacity and operation range, can fly from the truck to perform the last-mile package deliveries. The objective is to minimize the time to serve all the customers respecting every precedence constraint. The problem is shown to be NP-hard, and a lower bound on the optimal time to serve all the customers is constructed by using tools from graph theory. Then, integrating with a topological sorting technique, several heuristic task assignment algorithms are proposed to solve the task assignment problem. Numerical simulations show the superior performances of the proposed algorithms compared with popular genetic algorithms. Note to Practitioners - This paper presents several task assignment algorithms for the precedence-constrained package delivery for the team of a truck and a micro drone. The truck can carry the drone moving in a street network, while the drone completes the last-mile package deliveries. The practical contributions of this paper are fourfold. First, the precedence constraints on the ordering of the customers to be served are considered, which enables complex logistic scheduling for customers prioritized according to their urgency or importance. Second, the package delivery optimization problem is shown to be NP-hard, which clearly shows the need for creative approximation algorithms to solve the problem. Third, the constructed lower bound on the optimal time to serve all the customers helps to clarify for practitioners the limiting performance of a feasible solution. Fourth, the proposed task assignment algorithms are efficient and can be adapted for real scenarios

Automatic Disassembly Task Sequence Planning of Aircrafts at their End-of-Life

RÉSUMÉ Une prise de conscience des problèmes environnementaux à l'échelle mondiale ainsi que des avantages économiques a stimulé les chercheurs à trouver les possibilités de réutiliser et de recycler les produits en fin de vie. Chaque année plusieurs centaines d'avions atteignent globalement fin de leur navigabilité et doivent être retirés du service actif. De ce fait, une attention accrue est maintenant accordée à la fin de vie des avions. Désassemblage joue un rôle important dans la prise de décision de fin de vie. La faisabilité économique du processus de démontage avec beaucoup d'incertitudes est une préoccupation majeure limitant sa mise en oeuvre dans la pratique de l'industrie. De nombreuses recherches dans le domaine de la planification et des opérations de processus de démontage a été fait, qui visent de plus en plus la faisabilité économique du démontage avec la réduction des temps de démontage de proposer des séquences de démontage optimisées. Par conséquent, ces dernières années, de nombreux chercheurs ont publié des articles sur la planification de la séquence de démontage des produits en fin de vie qui est un problème NP-complet optimisation combinatoire. Néanmoins, il y a eu un peu d'attention à la planification de la séquence de démontage d'avions en fin de vie. Cette thèse aborde la planification de séquence de démontage des pièces réutilisables d'avions en fin de vie avant le démantèlement pour le recyclage. Puisque les composants récupérés vont être utilisés à nouveau, une approche non-destructive tout en respectant les instructions fournies dans le manuel d'entretien d'avion intitulé « Aircraft Maintenance Manuel » (AMM) pour le retrait des pièces est prise en considération. Ordonnancement de désassemblage dans cette recherche ne traite pas le séquençage le démontage des pièces comme dans d'autres études, mais il planifie séquence de tâches de démontage dans l'AMM. Une tâche de démontage consiste combinaison d'opérations pour la préparation du démontage ou le procède de démontage pour un ou plusieurs pièces. Tout d'abord, un modèle de séquençage de démontage est proposé par l'examen structure des tâches de démontage dans l'AMM. Ensuite, un code Matlab est développé qui lit la base de données énuméré des tâches et sous-tâches qui sont acquises à partir de l'AMM et génère la séquence de démontage des tâches et sous-tâches automatiquement en utilisant le modèle proposé. Le code est capable de générer des séquences de désassemblage de tâches pour n’importe quelle pièce sollicitée.----------ABSTRACT An awareness of the world’s environmental problems plus economic benefits has stimulated researchers to seek the opportunities to reuse and recycle end-of-life (EOL) products. Each year hundreds of aircraft globally reach end of their airworthiness and should be withdrawn from active service. Due to this fact, increased attention is now being paid to EOL of aircrafts. Disassembly plays an important role in EOL decision making. The economic feasibility of the disassembly process with lots of uncertainties is a main concern limiting its implementation in industry practice. Many researches in the field of disassembly process planning and operations has been done that aim increasing economic feasibility of disassembly with reducing disassembly times with proposing optimized disassembly sequences. Consequently, in recent years, many scholars have published articles on disassembly sequence planning of EOL products that is a NP-complete combinatorial optimization problem. Nevertheless, there has been a scant attention towards disassembly sequence planning of EOL aircrafts. This thesis addresses disassembly sequence planning of reusable components of EOL aircrafts before dismantling it for recycling. Since retrieved components are going to be used again, a nondestructive approach with respecting all instructions provided in aircraft maintenance manual (AMM) for removal of parts is taken into consideration. Disassembly scheduling in this work does not deal with scheduling disassembly of components as in other works but it schedules sequence of removal Tasks in AMM. A removal task consists combination of operations for preparation of disassembly or process of disassembly for a part or multiple parts. At first, a disassembly sequencing model with considering structure of disassembly tasks in AMM is proposed. Afterwards a Matlab code is developed which reads from enumerated database of tasks and subtasks that are acquired from AMM and generates disassembly sequence of tasks and subtasks automatically using the proposed model. The code is capable of generating disassembly sequences of tasks for any given removal task of solicited part. Finally, a greedy and an adaptive greedy algorithm are proposed to optimize disassembly sequence of tasks with minimizing changes in visited zones of disassembly operations. Results generated in Matlab code, suggests effectiveness of proposed adaptive greedy algorithm

Cooperative task assignment for multiple vehicles

Multi-vehicle systems have been increasingly exploited to accomplish difficult and complex missions, where effective and efficient coordinations of the vehicles can greatly improve the team's performance. Motivated by need from practice, we study the multi-vehicle task assignment in various challenging environments. We first investigate the task assignment for multiple vehicles in a time-invariant drift field. The objective is to employ the vehicles to visit a set of target locations in the drift field while trying to minimize the vehicles' total travel time. Using optimal control theory, a path planning algorithm is designed to generate the time-optimal path for a vehicle to travel between any two prescribed locations in a drift field. The path planning algorithm provides the cost matrix for the target assignment, and generates routes once the target locations are assigned to the vehicles. Using tools from graph theory, a lower bound on the optimal solution is found, which can be used to measure the proximity of a solution from the optimal. We propose several clustering-based task assignment algorithms in which two of them guarantee that all the target locations will be visited within a computable maximal travel time, which is at most twice of the optimal when the cost matrix is symmetric. In addition, we extend the multi-vehicle task assignment study in a time-invariant drift field with obstacles. The vehicles have different capabilities, and each kind of vehicles need to visit a certain type of target locations; each target location might have the demand to be visited more than once by different kinds of vehicles. A path planning method has been designed to enable the vehicles to move between two prescribed locations in a drift field with the minimal time while avoiding obstacles. This task assignment problem is shown to be NP-hard, and a distributed task assignment algorithm has been designed, which can achieve near-optimal solutions to the task assignment problem. Furthermore, we study the task assignment problem in which multiple dispersed heterogeneous vehicles with limited communication range need to visit a set of target locations while trying to minimize the vehicles' total travel distance. Each vehicle initially has the position information of all the targets and of those vehicles that are within its limited communication range, and each target demands a vehicle with some specified capability to visit it. We design a decentralized auction algorithm which first employs an information consensus procedure to merge the local information carried by each communication-connected vehicle subnetwork. Then, the algorithm constructs conflict-free target assignments for the communication-connected vehicles, and guarantees that the total travel distance of the vehicles is at most twice of the optimal when the communication network is initially connected. In the end we exploit the precedence-constrained task assignment problem for a truck and a micro drone to deliver packages to a set of dispersed customers subject to precedence constraints that specify which customers need to be visited before which other customers. The truck is restricted to travel in a street network and the micro drone, restricted by its loading capacity and operation range, can fly from the truck to perform the last mile package deliveries. The objective is to minimize the time to serve all the customers respecting every precedence constraint. The problem is shown to be NP-hard, and a lower bound on the optimal time to serve all the customers is constructed by using tools from graph theory. Integrating with a topological sorting technique, several heuristic task assignment algorithms are constructed to solve the task assignment problem

Prise en compte de la flexibilité des ressources humaines dans la planification et l’ordonnancement des activités industrielles

Le besoin croissant de réactivité dans les différents secteurs industriels face à la volatilité des marchés soulève une forte demande de la flexibilité dans leur organisation. Cette flexibilité peut être utilisée pour améliorer la robustesse du planning de référence d’un programme d’activités donné. Les ressources humaines de l’entreprise étant de plus en plus considérées comme le coeur des structures organisationnelles, elles représentent une source de flexibilité renouvelable et viable. Tout d’abord, ce travail a été mis en oeuvre pour modéliser le problème d’affectation multi-périodes des effectifs sur les activités industrielles en considérant deux dimensions de la flexibilité: L’annualisation du temps de travail, qui concerne les politiques de modulation d’horaires, individuels ou collectifs, et la polyvalence des opérateurs, qui induit une vision dynamique de leurs compétences et la nécessité de prévoir les évolutions des performances individuelles en fonction des affectations successives. La nature dynamique de l’efficacité des effectifs a été modélisée en fonction de l’apprentissage par la pratique et de la perte de compétence pendant les périodes d’interruption du travail. En conséquence, nous sommes résolument placés dans un contexte où la durée prévue des activités n’est plus déterministe, mais résulte du nombre des acteurs choisis pour les exécuter, en plus des niveaux de leur expérience. Ensuite, la recherche a été orientée pour répondre à la question : « quelle genre, ou quelle taille, de problème pose le projet que nous devons planifier? ». Par conséquent, les différentes dimensions du problème posé sont classées et analysés pour être évaluées et mesurées. Pour chaque dimension, la méthode d’évaluation la plus pertinente a été proposée : le travail a ensuite consisté à réduire les paramètres résultants en composantes principales en procédant à une analyse factorielle. En résultat, la complexité (ou la simplicité) de la recherche de solution (c’est-à-dire de l’élaboration d’un planning satisfaisant pour un problème donné) peut être évaluée. Pour ce faire, nous avons développé une plate-forme logicielle destinée à résoudre le problème et construire le planning de référence du projet avec l’affectation des ressources associées, plate-forme basée sur les algorithmes génétiques. Le modèle a été validé, et ses paramètres ont été affinés via des plans d’expériences pour garantir la meilleure performance. De plus, la robustesse de ces performances a été étudiée sur la résolution complète d’un échantillon de quatre cents projets, classés selon le nombre de leurs tâches. En raison de l’aspect dynamique de l’efficacité des opérateurs, le présent travail examine un ensemble de facteurs qui influencent le développement de leur polyvalence. Les résultats concluent logiquement qu’une entreprise en quête de flexibilité doit accepter des coûts supplémentaires pour développer la polyvalence de ses opérateurs. Afin de maîtriser ces surcoûts, le nombre des opérateurs qui suivent un programme de développement des compétences doit être optimisé, ainsi que, pour chacun d’eux, le degré de ressemblance entre les nouvelles compétences développées et les compétences initiales, ou le nombre de ces compétences complémentaires (toujours pour chacun d’eux), ainsi enfin que la façon dont les heures de travail des opérateurs doivent être réparties sur la période d’acquisition des compétences. Enfin, ce travail ouvre la porte pour la prise en compte future des facteurs humains et de la flexibilité des effectifs pendant l’élaboration d’un planning de référence. ABSTRACT : The growing need of responsiveness for manufacturing companies facing the market volatility raises a strong demand for flexibility in their organization. This flexibility can be used to enhance the robustness of a baseline schedule for a given programme of activities. Since the company personnel are increasingly seen as the core of the organizational structures, they provide the decision-makers with a source of renewable and viable flexibility. First, this work was implemented to model the problem of multi-period workforce allocation on industrial activities with two degrees of flexibility: the annualizing of the working time, which offers opportunities of changing the schedules, individually as well as collectively. The second degree of flexibility is the versatility of operators, which induces a dynamic view of their skills and the need to predict changes in individual performances as a result of successive assignments. The dynamic nature of workforce’s experience was modelled in function of learning-by-doing and of oblivion phenomenon during the work interruption periods. We firmly set ourselves in a context where the expected durations of activities are no longer deterministic, but result from the number and levels of experience of the workers assigned to perform them. After that, the research was oriented to answer the question “What kind of problem is raises the project we are facing to schedule?”: therefore the different dimensions of the project are inventoried and analysed to be measured. For each of these dimensions, the related sensitive assessment methods have been proposed. Relying on the produced correlated measures, the research proposes to aggregate them through a factor analysis in order to produce the main principal components of an instance. Consequently, the complexity or the easiness of solving or realising a given scheduling problem can be evaluated. In that view, we developed a platform software to solve the problem and construct the project baseline schedule with the associated resources allocation. This platform relies on a genetic algorithm. The model has been validated, moreover, its parameters has been tuned to give the best performance, relying on an experimental design procedure. The robustness of its performance was also investigated, by a comprehensive solving of four hundred instances of projects, ranked according to the number of their tasks. Due to the dynamic aspect of the workforce’s experience, this research work investigates a set of different parameters affecting the development of their versatility. The results recommend that the firms seeking for flexibility should accept an amount of extra cost to develop the operators’ multi functionality. In order to control these over-costs, the number of operators who attend a skill development program should be optimised, as well as the similarity of the new developed skills relative to the principal ones, or the number of the additional skills an operator may be trained to, or finally the way the operators’ working hours should be distributed along the period of skill acquisition: this is the field of investigations of the present work which will, in the end, open the door for considering human factors and workforce’s flexibility in generating a work baseline program

Considering the flexibility of human resources in planning and scheduling industrial activities

The growing need of responsiveness for manufacturing companies facing the market volatility raises a strong demand for flexibility in their organization. This flexibility can be used to enhance the robustness of a baseline schedule for a given programme of activities. Since the company personnel are increasingly seen as the core of the organizational structures, they provide the decision-makers with a source of renewable and viable flexibility. First, this work was implemented to model the problem of multi-period workforce allocation on industrial activities with two degrees of flexibility: the annualizing of the working time, which offers opportunities of changing the schedules, individually as well as collectively. The second degree of flexibility is the versatility of operators, which induces a dynamic view of their skills and the need to predict changes in individual performances as a result of successive assignments. The dynamic nature of workforce’s experience was modelled in function of learning-by-doing and of oblivion phenomenon during the work interruption periods. We firmly set ourselves in a context where the expected durations of activities are no longer deterministic, but result from the number and levels of experience of the workers assigned to perform them. After that, the research was oriented to answer the question “What kind of problem is raises the project we are facing to schedule?”: therefore the different dimensions of the project are inventoried and analysed to be measured. For each of these dimensions, the related sensitive assessment methods have been proposed. Relying on the produced correlated measures, the research proposes to aggregate them through a factor analysis in order to produce the main principal components of an instance. Consequently, the complexity or the easiness of solving or realising a given scheduling problem can be evaluated. In that view, we developed a platform software to solve the problem and construct the project baseline schedule with the associated resources allocation. This platform relies on a genetic algorithm. The model has been validated, moreover, its parameters has been tuned to give the best performance, relying on an experimental design procedure. The robustness of its performance was also investigated, by a comprehensive solving of four hundred instances of projects, ranked according to the number of their tasks. Due to the dynamic aspect of the workforce’s experience, this research work investigates a set of different parameters affecting the development of their versatility. The results recommend that the firms seeking for flexibility should accept an amount of extra cost to develop the operators’ multi functionality. In order to control these over-costs, the number of operators who attend a skill development program should be optimised, as well as the similarity of the new developed skills relative to the principal ones, or the number of the additional skills an operator may be trained to, or finally the way the operators’ working hours should be distributed along the period of skill acquisition: this is the field of investigations of the present work which will, in the end, open the door for considering human factors and workforce’s flexibility in generating a work baseline program