Hybrid Genetic Algorithm for Multi-Period Vehicle Routing Problem with Mixed Pickup and Delivery with Time Window, Heterogeneous Fleet, Duration Time and Rest Area

Most logistics industries are improving their technology and innovation in competitive markets in order to serve the various needs of customers more efficiently. However, logistics management costs are one of the factors that entrepreneurs inevitably need to reduce, so that goods and services are distributed to a number of customers in different locations effectively and efficiently. In this research, we consider the multi-period vehicle routing problem with mixed pickup and delivery with time windows, heterogeneous fleet, duration time and rest area (MVRPMPDDR). In the special case that occurs in this research, it is the rest area for resting the vehicle after working long hours of the day during transportation over multiple periods, for which with confidence no research has studied previously. We present a mixed integer linear programming model to give an optimal solution, and a meta-heuristic approach using a hybrid genetic algorithm with variable neighborhood search algorithm (GAVNS) has been developed to solve large-sized problems. The objective is to maximize profits obtained from revenue after deducting fuel cost, the cost of using a vehicle, driver wage cost, penalty cost and overtime cost. We prepared two algorithms, including a genetic algorithm (GA) and variable neighborhood search algorithm (VNS), to compare the performance of our proposed algorithm. The VNS is specially applied instead of the mutation operator in GA, because it can reduce duplicate solutions of the algorithms that increase the difficulty and are time-consuming. The numerical results show the hybrid genetic algorithm with variable neighborhood search algorithm outperforms all other proposed algorithms. This demonstrates that the proposed meta-heuristic is efficient, with reasonable computational time, and is useful not only for increasing profits, but also for efficient management of the outbound transportation logistics system

Vehicle routing problem with cross-docking as part of industry 4.0 logistics

The work presented in this paper has been supported by West Bohemia University in Pilsen (project No.SGS SGS-2021-022 - Financial (stock) markets, modeling and prediction of behavior).The trends associated with the onset of Industry 4.0 are obvious and require a prompt response from the company. An indisputable advantage is the use of the cross-docking strategy, which makes it possible to coordinate all logistics processes and achieve optimization of transport costs while maintaining minimal handling and storage. The goods are directly redistributed within the distribution system to specific customers according to their requirements without the need for storage. This logistic method is very often associated with various types of vehicle routing problem. It enables the introduction and use of Industry 4.0 principles. The aim of this contribution is to find out the possibilities of using Cross-docking within the vehicle routing problem. The output is a classification of five vehicle routing problems and their further breakdown, which are successfully connected with the idea of Cross-docking technology. This is a Capacitated vehicle routing problem with cross-docking, Open vehicle routing problem with cross-docking, Vehicle routing problem with cross-docking for multi-products, Multi-echelon distribution networks and Rich vehicle routing problem with cross-docking. Literature analysis shows that it is not an isolated technology but a tool offering a comprehensive logistics service connecting several processes. Offer various combinations of technologies in conjunction with vehicle routing problems to provide economic benefit and reduce the environmental impact of logistics chains

A comprehensive framework for sustainable closed-loop supply chain network design

Many companies face challenges in reducing their supply chain costs while increasing sustainability and customer service levels. A comprehensive framework for a sustainable closed-loop supply chain (CLSC) network is a practical solution to these challenges. Hence, for the first time, this study considers an integrated multio-bjective mixed-integer linear programming (MOMILP) model to design sustainable CLSC networks with cross-docking, location-inventory-routing, time window, supplier selection, order allocation, transportation modes with simultaneous pickup, and delivery under uncertainty. An intelligent simulation algorithm is proposed to produce CLSC network data with probabilistic distribution functions and feasible solution space. In addition, a fuzzy goal programming approach is proposed to solve the MOMILP model under uncertainty. Eight small and medium-size test problems are used to evaluate the performance of the proposed model with the simulated data in GAMS software. The results obtained from test problems and sensitivity analysis show the efficacy of the proposed model

Cross-Docking: A Proven LTL Technique to Help Suppliers Minimize Products\u27 Unit Costs Delivered to the Final Customers

This study aims at proposing a decision-support tool to reduce the total supply chain costs (TSCC) consisting of two separate and independent objective functions including total transportation costs (TTC) and total cross-docking operating cost (TCDC). The full-truckload (FT) transportation mode is assumed to handle supplier→customer product transportation; otherwise, a cross-docking terminal as an intermediate transshipment node is hired to handle the less-than-truckload (LTL) product transportation between the suppliers and customers. TTC model helps minimize the total transportation costs by maximization of the number of FT transportation and reduction of the total number of LTL. TCDC model tries to minimize total operating costs within a cross-docking terminal. Both sub-objective functions are formulated as binary mathematical programming models. The first objective function is a binary-linear programming model, and the second one is a binary-quadratic assignment problem (QAP) model. QAP is an NP-hard problem, and therefore, besides a complement enumeration method using ILOG CPLEX software, the Tabu search (TS) algorithm with four diversification methods is employed to solve larger size problems. The efficiency of the model is examined from two perspectives by comparing the output of two scenarios including; i.e., 1) when cross-docking is included in the supply chain and 2) when it is excluded. The first perspective is to compare the two scenarios’ outcomes from the total supply chain costs standpoint, and the second perspective is the comparison of the scenarios’ outcomes from the total supply chain costs standpoint. By addressing a numerical example, the results confirm that the present of cross-docking within a supply chain can significantly reduce total supply chain costs and total transportation costs

A Polyhedral Study of Mixed 0-1 Set

We consider a variant of the well-known single node fixed charge network flow set with constant capacities. This set arises from the relaxation of more general mixed integer sets such as lot-sizing problems with multiple suppliers. We provide a complete polyhedral characterization of the convex hull of the given set

The multi-depot VRP with vehicle interchanges

In real-world logistic operations there are a lot of situations that can be exploited to get better operational strategies. It is important to study these new alternatives, because they can represent significant cost reductions to the companies working with physical distribution. This thesis defines the Multi-Depot Vehicle Routing Problem with Vehicle Interchanges (MDVRPVI). In this problem, both vehicle capacities and duration limits on the routes of the drivers are imposed. To favor a better utilization of the available capacities and working times, it is allowed to combine pairs of routes at predefined interchange locations. The objective of this thesis is to analyze and solve the Multi-Depot Vehicle Routing Problem adding the possibility to interchange vehicles at predefined points. With this strategy, it is possible to reduce the total costs and the number of used routes with respect to the classical approach: The Multi-Depot Vehicle Routing Problem (MDVRP). It should be noted that the MDVRP is more challenging and sophisticated than the single-depot Vehicle Routing Problem (VRP). Besides, most exact algorithms for solving the classical VRP are difficult to adapt in order to solve the MDVRP (Montoya-Torres et al., 2015). From the complexity point of view, the MDVRPVI is NP-Hard, since it is an extension of the classical problem, which is already NP-Hard. We present a tight bound on the costs savings that can be attained allowing interchanges. Three integer programming formulations are proposed based on the classical vehicle-flow formulations of the MDVRP. One of these formulations was solved with a branch-and-bound algorithm, and the other two formulations, with branch-and-cut algorithms. Due to its great symmetry, the first formulation is only able to solve small instances. To increase the dimension of the instances used, we proposed two additional formulations that require one or more families of constraints of exponential size. In order to solve these formulations, we had to design and implement specific branch-and-cut algorithms. For these algorithms we implemented specific separation methods for constraints that had not previously been used in other routing problems. The computational experience performed evidences the routing savings compared with the solutions obtained with the classical approach and allows to compare the efficacy of the three solution methods proposed.En les operacions logístiques del món real es donen situacions que poden ser explotades per obtenir millors estratègies operacionals. És molt important estudiar aquestes noves alternatives, perquè poden representar una reducció significativa de costos per a les companyies que treballen en distribució de mercaderies. En aquesta tesi es defineix el Problema d'Enrutament de Vehicles amb Múltiples Dipòsits i Intercanvi de Vehicles (MDVRPVI). En aquest problema, es consideren tant la capacitat dels vehicles com els límits de duració de les rutes dels conductors. Per tal de millorar la utilització de les capacitats i temps de treball disponibles, es permet combinar parelles de rutes en punts d'intercanvi predefinits. L'objectiu d'aquesta tesi és analitzar i resoldre el problema d'Enrutament de Vehicles amb Múltiples Dipòsits, on es permet l'intercanvi de vehicles. Amb aquesta estratègia, és possible reduir els costos totals i el nombre de les rutes utilitzades respecte l'enfocament clàssic: el problema d'Enrutament de Vehicles amb Múltiples Dipòsits (MDVRP). Cal assenyalar que el MDRVP és més desafiant i sofisticat que el problema d'Enrutament de Vehicles d'un únic dipòsit (VRP). A més, molts algoritmes exactes per resoldre el VRP clàssic son complicats d'adaptar per resoldre el MDVRP (Montoya-Torres et al., 2015). Des del punt de vista de la complexitat, el MDRVPVI és NP-Dur, perquè és una extensió del problema clàssic, que també ho és. Presentem una cota ajustada de l'estalvi en els costos de distribució que es pot obtenir permetent els intercanvis. Es proposen tres formulacions de programació sencera basades en la formulació clàssica “vehicle-flow” del MDVRP. La primera formulació, degut a la seva grandària i la seva simetria, només permet resoldre instàncies molt petites. Per augmentar la dimensió de les instàncies abordables, es proposen dues formulacions addicionals que requereixen una o vàries famílies de restriccions de mida exponencial. Per això, per tal de resoldre el problema amb aquestes formulacions, ha calgut dissenyar i implementar sengles algorismes de tipus branch-and-cut. En aquests algorismes s'han implementat mètodes de separació específics per a les restriccions que no s'havien utilitzat prèviament en altres problemes de rutes. L’experiència computacional realitzada evidencia els estalvis obtinguts comparació amb les solucions corresponents l'enfocament clàssic. També es compara l’eficàcia dels tres mètodes propostes a l'hora de resoldre el problema.Postprint (published version