A Tabu Search algorithm for the vehicle routing problem with discrete split deliveries and pickups

The Vehicle Routing Problem with Discrete Split Deliveries and Pickups is a variant of the Vehicle Routing Problem with Split Deliveries and Pickups, in which customers’ demands are discrete in terms of batches (or orders). It exists in the practice of logistics distribution and consists of designing a least cost set of routes to serve a given set of customers while respecting constraints on the vehicles’ capacities. In this paper, its features are analyzed. A mathematical model and Tabu Search algorithm with specially designed batch combination and item creation operation are proposed. The batch combination operation is designed to avoid unnecessary travel costs, while the item creation operation effectively speeds up the search and enhances the algorithmic search ability. Computational results are provided and compared with other methods in the literature, which indicate that in most cases the proposed algorithm can find better solutions than those in the literature

The heterogeneous fleet vehicle routing problem with light loads and overtime: Formulation and population variable neighbourhood search with adaptive memory

In this paper we consider a real life Vehicle Routing Problem inspired by the gas delivery industry in the United Kingdom. The problem is characterized by heterogeneous vehicle fleet, demand-dependent service times, maximum allowable overtime and a special light load requirement. A mathematical formulation of the problem is developed and optimal solutions for small sized instances are found. A new learning-based Population Variable Neighbourhood Search algorithm is designed to address this real life logistic problem. To the best of our knowledge Adaptive Memory has not been hybridized with a classical iterative memoryless method. In this paper we devise and analyse empirically a new and effective hybridization search that considers both memory extraction and exploitation. In terms of practical implications, we show that on a daily basis up to 8% cost savings on average can be achieved when overtime and light load requirements are considered in the decision making process. Moreover, accommodating for allowable overtime has shown to yield 12% better average utilization of the driver's working hours and 12.5% better average utilization of the vehicle load, without a significant increase in running costs. We also further discuss some managerial insights and trade-offs

Évaluation de la performance de stratégies logistiques inverses dans le secteur de la vente au détail par la simulation à base d’agents

RÉSUMÉ : Une bonne gestion de la chaîne d’approvisionnement est primordiale au bon contrôle des coûts d’une entreprise et à l’amélioration de la performance. Le désir de retirer un maximum de chaque dollar investi pousse les entreprises à devoir constamment réévaluer la performance des procédures établies. Devant la complexité amenée par la chaîne d’approvisionnement, ce mémoire propose une approche de simulation à base d’agents afin d’évaluer la performance de plusieurs stratégies logistiques pour Renaissance, un organisme à but non-lucratif oeuvrant dans le secteur de la vente au détail d’articles usagés. L’organisme se trouve dans un contexte urbain en forte croissance et doit planifier de manière efficace ses opérations afin d’effectuer à la fois des collectes et des livraisons à chaque site. La technique de simulation à base d’agents s’est avérée efficace afin d’effectuer, dans un premier temps, un diagnostic des opérations actuelles et, dans un deuxième temps, l’évaluation de stratégies logistiques potentielles selon plusieurs scénarios de croissance. Les stratégies évaluées concernent soit des modifications dans la gestion de la flotte de camions, soit dans le moment de visite des sites ou bien dans un changement relié à la procédure de collecte et livraison des sites. Les indicateurs de performance majeurs utilisés sont la distance parcourue, le temps requis par jour et les émissions de CO2. En logistique verte, ce mémoire est également une autre application démontrant qu’il est possible d’utiliser les bases de données d’émissions de CO2 afin de simuler les implications environnementales de scénarios en fonction des types de camions et cycles de conduite. Les principales conclusions sont que la réduction du temps voyagé et de la distance parcourue implique souvent une hausse des émissions en CO2, à cause de l’utilisation de plus gros camions. Également, les contraintes d’accessibilité des sites et la flotte de camions actuellement utilisée entraînent une réduction de la performance logistique de l’ordre de 10% à 25%. Dans un autre ordre d’idées, la stratégie de visite des sites la nuit peut entraîner une diminution du temps moyen requis par jour d’environ 10%. Or, les restrictions municipales sur l’accès à certains sites par des camions durant la nuit limitent le potentiel de bénéfices amené par cette stratégie. À court-terme, la meilleure stratégie porte sur la modification de la flotte actuelle pour utiliser deux camions 36’ pour visiter aussi les centres de dons par opposition aux magasins seulement. Cette stratégie pourrait amener des bénéfices de l’ordre de 10% à 20% sur le temps et la distance totale, en n’impliquant qu’une minime hausse des émissions de CO2.----------ABSTRACT : A good supply chain management is essential in order to control costs and to ensure business success. The desire to maximize the return on investment forces companies to continuously review the procedures in place and their performance in order to confirm that they still are the most appropriate. Considering the complexities incurred by supply chain management, this paper proposes to use an agent-based simulation model approach to evaluate the performance of multiple potential logistics strategies for Renaissance, an non-profit organization in the secondhand retail business. This organization faces a strong growth in an urban context and has to efficiently plan its operations to both collect and deliver goods at every site. The agent-based simulation technique has proven to be capable to, in the first place, make an assessment of the current operations and then to evaluate potential logistics strategies in different growth scenarios. Envisaged strategies concern modifications either to the trucks fleet, to the time of sites visit or to the procedure in place to collect and deliver goods. The main key performance indicators used are the time per day, the distance travelled and the CO2 emissions. Also, in green logistics, this paper serves as another practical application of the possibility to use CO2 emissions databases to simulate environmental implications of scenarios, based on the types of trucks used and the drive cycles. The main conclusions of this paper are that decreasing time and distance travelled usually comes with an increase of CO2 emissions, due to the use of bigger trucks. Also, the current sites’ accessibility and fleet constraints affect the logistics performance by 10% to 25%. With regards to the strategies, visiting sites at night has the potential to decrease the travelling time by 10%. However, current municipal restrictions restraining trucks’ accessibility at night limit the benefits of this strategy. The best short-term strategy consists of the modification of the current fleet usage to use two 36’ trucks to visit both donation centers and stores, as opposed to only stores. This strategy could potentially bring 10% to 20% benefits of time and distance, while having only a minimal impact on CO2 emissions

The Vehicle Routing Problem with Restricted Mixing of Deliveries and Pickups

The vehicle routing problem with deliveries and pickups is one of the main problems within reverse logistics. This paper focuses on an important assumption that divides the literature on the topic, namely the restriction that all deliveries must be completed before pickups can be made. A generalised model is presented, together with a mathematical formulation and its resolution. The latter is carried out by adopting a suitable implementation of the reactive tabu search metaheuristic. Results show that significant savings can be achieved by allowing a mixture of delivery and pickup loads on-board and yet not incurring delays and driver inconvenience

Meta-Heuristics for the Multiple Trip Vehicle Routing Problem with Backhauls

With the growing and more accessible computational power, the demand for robust and sophisticated computerised optimisation is increasing for logistical problems. By making good use of computational technologies, the research in this thesis concentrates on efficient fleet management by studying a class of vehicle routing problems and developing efficient solution algorithms. The literature review in this thesis looks at VRPs from various development angles. The search reveals that from the problem modelling side clear efforts are made to bring the classical VRP models closer to reality by developing various variants. However, apart from the real VRP applications (termed as 'rich' VRPs), it is also noticeable that these classical VRP based variants address merely one or two additional characteristics from the real routing problem issues, concentrating on either operational (fleet management) or tactical (fleet acquisition) aspects. This thesis certainly hopes to add to one of those good efforts which have helped in bringing the VRPs closer to reality through addressing both the operational as well as the tactical aspects. On the solution methodologies development side, the proposed research noted some considerable and impressive developments. Although, it is well established that the VRPs belong to the NP-hard combinatorial class of problems, there are considerable efforts on the development of exact methods. However the literature is full of a variety of heuristic methodologies including the classical and the most modern hybrid approaches. Among the hybrid approaches, the most recent one noted is mat-heuristics that combine heuristics and mathematical programming techniques to solve combinatorial optimisation problems. The mat-heuristics approaches appear to be comparatively in its infant age at this point in time. However this is an exciting area of research which seeks more attention in the literature. Hence, a good part of this research is devoted to the development of a hybrid approach that combines heuristics and mathematical programming techniques. When reviewing the specific literature on the VRP problems focused in this thesis, the vehicle routing problem with backhauls (VRPB) and the multiple trip vehicle routing problem (MT-VRP), there is not sufficient development on the problem modelling side in terms of bringing these two problems closer to the reality. Hence, to fill the gap this thesis introduces and investigates a new variant, the multiple trip vehicle routing problem with backhauls (MT-VRPB) that combines the above two variants of the VRP. The problem is first described thoroughly and a new ILP (Integer Linear Programming) mathematical formulation of the MT-VRPB along with its possible variations is presented. The MT-VRPB is then solved optimally by using CPLEX along with providing an illustrative example showing the validation of the mathematical formulation. As part of the contribution, a large set of MT-VRPB data instances is created which is made available for future benchmarking. The CPLEX implementation produced optimal solutions for a good number of small and medium size data instances of the MT-VRPB and generated lower bounds for all instances. The CPLEX success may be considered as modest, but the produced results proved very important for the validation of the heuristic results produced in the thesis. To solve the larger instances of the MT-VRPB, a two level VNS algorithm called 'Two-Level VNS' is developed. It was noticed from the literature that the choice of using VNS for the VRPs has increased in recent literature due to its simplicity and speed. However our initial experiments with the classical VNS indicated that the algorithm is more inclined towards the intensification side. Hence, the Two-Level VNS is designed to obtain a maximum balance of the diversification and the intensification during the search process. It is achieved by incorporating a sub-set of neighbourhood structures and a sus-set of local search refinement routines and hence, a full set of neighbourhood structures and a full set of local search refinement routines at two levels of the algorithm respectively. The algorithm found very encouraging results when compared with the solutions found by CPLEX. These findings in this thesis demonstrate the power of VNS yet again in terms of its speed, simplicity and efficiency. To investigate this new variant further, we developed an algorithm belonging to the new class of the hybrid methodologies, i.e., mat-heuristics. A hybrid collaborative sequential mat-heuristic approach called the CSMH to solve the MT-VRPB is developed. The exact method approach produced in Chapter 4 is then hybridised with the Two-Level VNS algorithm developed in Chapter 5. The overall performance of the CSMH remained very encouraging in terms of the solution quality and the time taken on average compared with the CPLEX and the Two-Level VNS meta-heuristic. To demonstrate the power and effectiveness of our methodologies, we tested the designed algorithms on the two special versions of the VRP (i.e., VRPB and MT-VRP) to assess whether they are efficient and dynamic enough to solve a range of VRP variants. Hence the Two-Level VNS and the CSMH algorithms developed to solve the MT-VRPB are adapted accordingly and implemented to solve the two above variants separately. The algorithms produced very competitive results for the benchmark data sets when compared to the best known solutions from the literature. The successful implementations of these algorithms on the three VRP models with only minor amendments prove their generalizability and their robustness. The results in this research show that significant cost savings could be obtained by choosing the right fleet size and better vehicle utilisations with multiple trips and backhauling. Hence, the research proved the justification of studying this interesting combination. Moreover, the problem modelling, efficient algorithm design and implementation, and the research results reveal some vital information and implications from the managerial point of view in terms of making the tactical (fleet acquisition) and the operational (fleet management) decisions in a more informative manner

Horizontale en verticale samenwerking in distributieketens met cross-docks

Logistiek dienstverleners staan voor grote uitdagingen op het gebied van duurzaamheid, in het bijzonder vanwege de steeds kleiner wordende zendingen die just-in-time bij de klant moeten worden afgeleverd. Samenwerking tussen partners in de distributieketen en met concurrenten daarbuiten biedt kansen om deze uitdagingen het hoofd te bieden. Dit proefschrift richt zich op samenwerkingsvormen in distributieketens met cross-docks. Cross-docks zijn logistieke centra die bedrijven in staat stellen om kleine zendingen gegroepeerd te transporteren zonder dat daarvoor tussentijdse opslag nodig is. In een cross-dock worden goederen direct van inkomende naar uitgaande vrachtwagens verplaatst. Het succesvol toepassen van cross-docking vereist verticale samenwerking tussen partners in opeenvolgende stadia van de distributieketen. Horizontale samenwerking ontstaat tussen mogelijk concurrerende bedrijven die vergelijkbare activiteiten in verschillende distributieketens uitvoeren. Dit proefschrift presenteert theoretische modellen voor horizontale en verticale samenwerking in distributieketens met cross-docks en bestudeert oplossingsmethodieken waarmee de duurzaamheid van deze ketens kan worden verbeterd. Daarvoor worden concepten uit de vakgebieden informatiesystemen, Operations Research en Supply Chain Management gecombineerd. De in dit proefschrift beschreven classificatie van wiskundige cross-docking modellen onthult nieuwe onderzoeksvragen gericht op een betere afstemming tussen interne cross-dock processen en ketenlogistiek. Een simulatiestudie illustreert hoe geringe aanpassingen in de ketenlogistiek tot grote prestatieverbeteringen in het cross-dock leiden. Op het gebied van horizontale samenwerking is een methode ontwikkeld die de uitwisseling van ladingen tussen transporteurs systematiseerd. Een reeks casussen toont aan dat doorbraken in ICT ontwikkeling nodig zijn om samenwerkende transporteurs in staat te stellen gezamenlijk planningsbeslissingen te nemen