Pengembangan Model Blood Mobile Collection Routing Problem (BMCRP) pada Proses Pengumpulan Darah

This research develop a model of blood mobile collection using blood donor vehicle efficiently by determining the optimal route of blood collection to the points of blood collection. The model developed in the form of mixed integer nonlinear programming (MINLP) and this model is called Blood Mobile Collection Routing Problem (BMCRP). The purpose of this model is to minimize the total distance of the blood collection routing process in which each place of blood collection has the opening hours and the closing time (time windows) and the service time in each place. This study considers the blood age (spoilage time) for 6 hours to ensure blood quality. The mathematical model is then verified to determine whether the solution is in accordance with the characteristics of BMCRP. Verification is done by solving Blood Mobile Collection Routing small cases. The simulation of solving BMCRP is done by generating eight hypothetical data sets of small cases based on vehicle routing data problems with different characteristics. Verification of BMCRP uses LINGO software. From the simulation results, the BMCRP model can obtain optimal solutions with minimum total distance travelled and does not violate any constraints on BMCRP

Pengembangan Model Blood Mobile Collection Routing Problem (BMCRP) pada Proses Pengumpulan Darah

This research develop a model of blood mobile collection using blood donor vehicle efficiently by determining the optimal route of blood collection to the points of blood collection. The model developed in the form of mixed integer nonlinear programming (MINLP) and this model is called Blood Mobile Collection Routing Problem (BMCRP). The purpose of this model is to minimize the total distance of the blood collection routing process in which each place of blood collection has the opening hours and the closing time (time windows) and the service time in each place. This study considers the blood age (spoilage time) for 6 hours to ensure blood quality. The mathematical model is then verified to determine whether the solution is in accordance with the characteristics of BMCRP. Verification is done by solving Blood Mobile Collection Routing small cases. The simulation of solving BMCRP is done by generating eight hypothetical data sets of small cases based on vehicle routing data problems with different characteristics. Verification of BMCRP uses LINGO software. From the simulation results, the BMCRP model can obtain optimal solutions with minimum total distance travelled and does not violate any constraints on BMCRP

A light-touch routing optimization tool (RoOT) for vaccine and medical supply distribution in Mozambique.

Planning vaccine distribution in rural and urban poor communities is challenging, due in part to inadequate vehicles, limited cold storage, road availability, and weather conditions. The University of Washington and VillageReach jointly developed and tested a user-friendly, Excel spreadsheet based optimization tool for routing and scheduling to efficiently distribute vaccines and other medical commodities to health centers across Mozambique. This paper describes the tool and the process used to define the problem and obtain feedback from users during the development. The distribution and routing tool, named route optimization tool (RoOT), uses an indexing algorithm to optimize the routes under constrained resources. Numerical results are presented using five datasets, three realistic and two artificial datasets. RoOT can be used in routine or emergency situations, and may be easily adapted to include other products, regions, or logistic problems

The vehicle routing problem and its intersection with cross-docking

To close a gap identified in the vehicle routing academic literature a theoretical link is established between the Vehicle Routing Problem and Cross Docking. A model for the vehicle routing problem with shipment consolidation (VRPC), in which vehicles can consolidate cargo among one another at a customer’s location, is presented. With shipment consolidation, vehicles can deliver product to a customer, transfer product to another vehicle, or both. Three main models are proposed: the vehicle routing problem with shipment consolidation (VRPC) which improves routing performance by allowing vehicles to consolidate cargo at any customer site; a metaheuristic to explore the effects of the VRPC over large scale problems; and the Vehicle Routing Problem with Shipment Consolidation and Time Windows (VRPCTW) to further study the proposed concept under extended, more constrained circumstances. Computational experiments are developed and solved to optimality where possible using OPL and Java in conjunction with CPLEX and show that the proposed concept of shipment consolidation can provide significant savings in objective function value when compared to previously published models

Traveler Centric Trip Planning: A situation-Aware System

Trip planning is a well cited problem for which various solutions have been reported in the literature. This problem has been typically addressed, to a large extent, as a shortest distance path planning problem. In some scenarios, the concept of shortest path is extended to reflect temporal objectives and/or constraints. This work takes an alternative perspective to the trip planning problem in the sense it being situation aware. Thus, allowing multitudes of traveler centric objectives and constraints, as well as aspects of the environment as they pertain to the trip and the traveler. The work in this thesis introduces TSADA (Traveler Situation Awareness and Decision Aid) system. TSADA is designed as a modular system that combines linguistic situation assessment with user-centric decision-making. The trip planning problem is modeled as a graph G. The objective is to find a route with the minimum cost. Both hard and soft objective/attributes are incorporated. Soft objective/attributes such as safety, speed and driving comfortability are described using a linguistic framework and processed using hierarchical fuzzy inference engine. A user centric situation assessment is used to compute feasible routes and map them into route recommendation scheme: recommended, marginally recommended, and not recommended. In this work, we introduce traveler's doctrines concept. This concept is proposed to make the process of situation assessment user centric by being driven by the doctrine that synthesizes the user's specific demands. Hard attributes/objectives, such as the time window and trip monitory allowances, are included in the process of determining the final decision about the trip. We present the underline mathematical formulation for this system and explain the working of the proposed system to achieve optimal performance. Results are introduced to show how the system performs under a wide range of scenarios. The thesis is concluded with a discussion on findings and recommendations for future work

Une heuristique de recherche à voisinage variable pour le problème du voyageur de commerce avec fenêtres de temps

Nous adaptons une heuristique de recherche à voisinage variable pour traiter le problème du voyageur de commerce avec fenêtres de temps (TSPTW) lorsque l'objectif est la minimisation du temps d'arrivée au dépôt de destination. Nous utilisons des méthodes efficientes pour la vérification de la réalisabilité et de la rentabilité d'un mouvement. Nous explorons les voisinages dans des ordres permettant de réduire l'espace de recherche. La méthode résultante est compétitive avec l'état de l'art. Nous améliorons les meilleures solutions connues pour deux classes d'instances et nous fournissons les résultats de plusieurs instances du TSPTW pour la première fois.We adapt a general variable neighborhood search heuristic to solve the traveling salesman problem with time windows (TSPTW) where the objective is to minimize the completion time. We use efficient methods to check the feasibility and the profitability of a movement. We use a specific order to reduce the search space while exploring the neighborhoods. The resulting method is competitive with the state-of-the-art. We improve the best known solutions for two classes of instances and provide the results of multiple instances of TSPTW for the first time

Problème de déploiement de ressources dans le cas des feux de forêts majeurs : opérations aériennes

Chaque année le feu brûle quelques dizaines de milliers d’hectares de forêts québécoises. Le coût annuel de prévention et de lutte contre les feux de forêts au Québec est de l’ordre de plusieurs dizaines de millions de dollars. Le présent travail contribue à la réduction de ces coûts à travers l’automatisation du processus de planification des opérations de suppression des feux de forêts majeurs. Pour ce faire, un modèle mathématique linéaire en nombres entiers a été élaboré, résolu et testé; introduisant un nouveau cas particulier à la littérature des Problèmes de Tournées de Véhicules (VRP). Ce modèle mathématique concerne le déploiement aérien des ressources disponibles pour l’extinction des incendies. Le modèle élaboré a été testé avec CPLEX sur des cas tirés de données réelles. Il a permis de réduire le temps de planification des opérations d’extinction des feux de forêts majeurs de 75% dans les situations courantes.Each year, the fire burns large areas of forests in the province of Quebec. The annual costs of prevention and firefighting in Quebec may attain tens of millions of dollars. This project contributes to the decreasing of those costs through the computerization of the transportation planning process of material and human resources during major forest fires extinguishing. In order to achieve that, the resource transportation process was mathematically modeled. The integer linear mathematical model developed in this project has been resolved and tested; it introduces a new case to the literature of Vehicle Routing Problem (VRP). The model developed was tested with CPLEX based on data from real cases. It has reduced the planning time of extinguishing operations by 75%