scholarly journals A mixed integer programming model for a continuous move transportation problem with service constraints

2017 ◽  
Vol 7 (13) ◽  
Author(s):  
J. Fabián López
Keyword(s):  
Vehicle Routing ◽  
Real World ◽  
Large Scale ◽  
Programming Model ◽  
Time Windows ◽  
Mixed Integer ◽  
Pickup And Delivery ◽  
Np Hard ◽  
Routing Problem ◽  
Service Constraints

Key words: Genetic algorithms, logistics routing, metaheuristics, scheduling, time windowsAbstract. We consider a Pickup and Delivery Vehicle Routing Problem (PDP) commonly encountered in real-world logistics operations. The problem involves a set of practical complications that have received little attention in the vehicle routing literature. In this problem, there are multiple vehicle types available to cover a set of pickup and delivery requests, each of which has pickup time windows and delivery time windows. Transportation orders and vehicle types must satisfy a set of compatibility constraints that specify which orders cannot be covered by which vehicle types. In addition we include some dock servicecapacity constraints as is required on common real world operations. This problem requires to be attended on large scale instances (orders ≥ 500), (vehicles ≥ 150). As a generalization of the traveling salesman problem, clearly this problem is NP-hard. The exact algorithms are too slow for large scale instances. The PDP-TWDS is both a packing problem (assign order tovehicles), and a routing problem (find the best route for each vehicle). We propose to solve the problem in three stages. The first stage constructs initials solutions at aggregate level relaxing some constraints on the original problem. The other two stages imposes time windows and dock service constraints. Our results are favorable finding good quality solutions in relatively short computational times.Palabras claves. Algoritmos genéticos, logística de ruteo, metahurística, programación, ventana de horarioResumen. En la solución de problemas combinatorios, es importante evaluar el costobeneficio entre la obtención de soluciones de alta calidad en detrimento de los recursos computacionales requeridos. El problema planteado es para el ruteo de un vehículo con entrega y recolección de producto y con restricciones de ventana de horario. En la práctica, dicho problema requiere ser atendido con instancias de gran escala (nodos ≥100). Existe un fuerte porcentaje de ventanas de horario activas (≥90%) y con factores de amplitud ≥75%. El  problema es NP-hard y por tal motivo la aplicación de un método de solución exacta para resolverlo en la práctica, está limitado por el tiempo requerido para la actividad de ruteo. Se propone un algoritmo genético especializado, el cual ofrece soluciones de buena calidad (% de optimalidad aceptables) y en tiempos de ejecución computacional que hacen útil su aplicación en la práctica de la logística. Para comprobar la eficacia de la propuesta algorítmica se desarrolla un diseño experimental el cual hará uso de las soluciones óptimas obtenidas mediante un algoritmo de ramificación y corte sin límite de tiempo. Los resultados son favorables.

scholarly journals POPMUSIC for a real-world large-scale vehicle routing problem with time windows

2009 ◽  
Vol 60 (7) ◽  
pp. 934-943 ◽  
Author(s):  
A Ostertag ◽  
K F Doerner ◽  
R F Hartl ◽  
E D Taillard ◽  
P Waelti
Keyword(s):  
Vehicle Routing ◽  
Real World ◽  
Vehicle Routing Problem ◽  
Large Scale ◽  
Time Windows ◽  
Routing Problem

scholarly journals Multidepot Heterogeneous Vehicle Routing Problem for a Variety of Hazardous Materials with Risk Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Bochen Wang ◽  
Qiyuan Qian ◽  
Zheyi Tan ◽  
Peng Zhang ◽  
Aizhi Wu ◽  
...  
Keyword(s):  
Risk Analysis ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Large Scale ◽  
Programming Model ◽  
Hazardous Materials ◽  
Mixed Integer ◽  
Small Scale ◽  
Routing Problem ◽  
Heterogeneous Vehicle Routing Problem

This study investigates a multidepot heterogeneous vehicle routing problem for a variety of hazardous materials with risk analysis, which is a practical problem in the actual industrial field. The objective of the problem is to design a series of routes that minimize the total cost composed of transportation cost, risk cost, and overtime work cost. Comprehensive consideration of factors such as transportation costs, multiple depots, heterogeneous vehicles, risks, and multiple accident scenarios is involved in our study. The problem is defined as a mixed integer programming model. A bidirectional tuning heuristic algorithm and particle swarm optimization algorithm are developed to solve the problem of different scales of instances. Computational results are competitive such that our algorithm can obtain effective results in small-scale instances and show great efficiency in large-scale instances with 70 customers, 30 vehicles, and 3 types of hazardous materials.

scholarly journals Routing Optimisation of Urban Medical Waste Recycling Network considering Differentiated Collection Strategy and Time Windows

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jiajing Gao ◽  
Haolin Li ◽  
Jingwen Wu ◽  
Junyan Lyu ◽  
Zheyi Tan ◽  
...  
Keyword(s):  
Large Scale ◽  
Programming Model ◽  
Time Windows ◽  
Computation Time ◽  
Waste Recycling ◽  
Medical Waste ◽  
Third Party ◽  
Mixed Integer ◽  
Routing Problem ◽  
Solution Approach

The increasing gap between medical waste production and disposal stresses the urgency of further development of urban medical waste recycling. This paper investigates an integrated optimisation problem in urban medical waste recycling network. It combines the vehicle routing problem of medical facilities with different requirements and the collection problem of clinics’ medical waste to the affiliated hospital. To solve this problem, a compact mixed-integer linear programming model is proposed, which takes account of the differentiated collection strategy and time windows. Since the medical waste recycling operates according to a two-day pattern, the periodic collection plan is also embedded in the model. Moreover, we develop a particle swarm optimisation (PSO) solution approach for problem-solving. Numerical experiments are also conducted to access the solution efficiency of the proposed algorithm, which can obtain a good solution in solving large-scale problem instances within a reasonable computation time. Based on the results, some managerial implications can be recommended for the third-party recycling company.

scholarly journals A model for the time dependent vehicle routing problem with time windows under traffic conditions with intelligent travel times

2021 ◽  
Author(s):  
Saeed Khanchehzarrin ◽  
Maral Shahmizad ◽  
Iraj Mahdavi ◽  
Nezam Mahdavi-Amiri ◽  
Peiman Ghasemi
Keyword(s):  
Travel Time ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Programming Model ◽  
Time Windows ◽  
Time Dependent ◽  
Mixed Integer ◽  
Travel Times ◽  
Routing Problem ◽  
Traffic Conditions

A new mixed-integer nonlinear programming model is presented for the time-dependent vehicle routing problem with time windows and intelligent travel times. The aim is to minimize fixed and variable costs, with the assumption that the travel time between any two nodes depends on traffic conditions and is considered to be a function of vehicle departure time. Depending on working hours, the route between any two nodes has a unique traffic parameter. We consider each working day to be divided into several equal and large intervals, termed as a scenario. Here, allowing for long distances between some of the nodes, travel time may take more than one scenario, resulting in resetting the scenario at the start of each large interval. This repetition of scenarios has been used in modeling and calculating travel time. A tabu search optimization algorithm is devised for solving large problems. Also, after linearization, a number of random instances are generated and solved by the CPLEX solver of GAMS to assess the effectiveness of our proposed algorithm. Results indicate that the initial travel time is estimated appropriately and updated properly in accordance with to the repeating traffic conditions.

scholarly journals A mixed-integer linear programming model for the selective full-truckload multi-depot vehicle routing problem with time windows

2021 ◽  
Vol 10 (4) ◽  
pp. 471-486 ◽  
Author(s):  
Karim EL Bouyahyiouy ◽  
Adil Bellabdaoui
Keyword(s):  
Linear Programming ◽  
Vehicle Routing ◽  
Integer Linear Programming ◽  
Vehicle Routing Problem ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Time Windows ◽  
Mixed Integer ◽  
Data Set ◽  
Routing Problem

This article has studied a full truckload transportation problem in the context of an empty return scenario, particularly an order selection and vehicle routing problem with full truckload, multiple depots and time windows (SFTMDVRPTW). The aim is to develop a solution where a set of truck routes serves a subset of selected transportation demands from a number of full truckload orders to maximize the total profit obtained from those orders. Each truck route is a chain of selected demands to serve, originating at a departure point and terminating at an arriving point of trucks in a way that respects the constraints of availability and time windows. It is not mandatory to serve all orders, and only the profitable ones are selected. In this study, we have formulated the SFTMDVRPTW as a mixed-integer linear programming (MILP) model. Finally, Computational results are conducted on a new data set that contains thirty randomly generated problem instances ranging from 16 to 30 orders using the CPLEX software. The findings prove that our model has provided good solutions in a reasonable time.

scholarly journals Transportation Risk Control of Waste Disposal in the Healthcare System with Two-Echelon Waste Collection Network

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Haolin Li ◽  
Yi Hu ◽  
Junyan Lyu ◽  
Hao Quan ◽  
Xiang Xu ◽  
...  
Keyword(s):  
Healthcare System ◽  
Large Scale ◽  
Programming Model ◽  
Time Windows ◽  
Decision Support Tool ◽  
Mixed Integer ◽  
Waste Collection ◽  
Routing Problem ◽  
Support Tool ◽  
Transportation Risk

This paper investigates a vehicle routing problem arising in the waste collection of the healthcare system with the concern of transportation risk. Three types of facilities abstracted from the health system are investigated in this paper, namely, facilities with collection points, facilities without collection points, and small facilities. Two-echelon collection mode is applied in which the waste generated by small facilities is first collected by collection points, and then transferred to the recycling centre. To solve this problem, we propose a mixed-integer linear programming model considering time windows and vehicle capacity, and we use particle swarm optimisation (PSO) algorithm for solving large-scale problems. Numerical experiments show the capability of the proposed algorithm. Sensitivity analysis is conducted to investigate the influence of facilities with collection points and the collection routes. This research can provide a decision support tool for the routing of waste collection in the healthcare system.

scholarly journals Vehicle Routing and Scheduling Problem for a multi-period, multi-perishable product system with time window: A Case study

2017 ◽  
Vol 5 (2) ◽  
pp. 45 ◽  
Author(s):  
Alireza Rashidi Komijan ◽  
Danial Delavari
Keyword(s):  
Vehicle Routing ◽  
Time Window ◽  
Programming Model ◽  
Transportation Costs ◽  
Mixed Integer ◽  
Pickup And Delivery ◽  
Routing Problem ◽  
Routing And Scheduling ◽  
Perishable Product ◽  
Proposed Model

<div data-canvas-width="542.172"><p>The well-known Vehicle Routing Problem (VRP) is to find proper sequence of routes in order to minimize transportation costs. In this paper, a mixed-integer programming model is presented for a food distributer company and the model outputs are to determine the optimal routes and amount of pickup and delivery. In the objective function, the costs of transportation, holding, tardiness and earliness are considered simultaneously. The proposed model with respect to real conditions is multi-period and has two different time periods: one for dispatching vehicles to customers and suppliers and the other for receiving  customers’ orders. Time window and split pickup and delivery are considered for perishable products. The proposed model is  nonlinear and will be linearized using exact techniques. At the end, model is solved using GAMS and the sensitivity analysis  is performed. The results indicate that the trend of changes in holding and transportation costs in compared to tardiness and  earliness costs are closed together and are not so sensitive to demand changes.</p></div>

Model and Algorithm for Vehicle Routing Problem with Time Windows and a Limited Number of Vehicles

2012 ◽  
Vol 482-484 ◽  
pp. 2322-2326 ◽  
Author(s):  
Yong Ji Jia ◽  
Chang Jun Wang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Programming Model ◽  
Search Algorithm ◽  
Time Windows ◽  
Real Life ◽  
Mixed Integer ◽  
Routing Problem ◽  
Number Of Customers

In this paper, a useful variant of the vehicle routing problem, Vehicle Routing Problem with Time Windows and a limited number of vehicles (m-VRPTW) is given. The problem is to serve a number of customers at minimum cost by using a limited number of vehicles, without violating the time window constraint and the vehicle capacity constraint. The feasible solution of m-VRPTW may contain some unserved customers and third-party vehicles, such as taxies, are hired to serve these unserved customers. The mixed integer programming model of m-VRPTW is proposed and a two-phase algorithm based on insertion algorithm and tabu search algorithm is proposed to solve it. Experimental results show that our algorithm can yield effective and efficient solution and be capable of dealing with the m-VRPTW problems in real life conditions.

scholarly journals A Two-Echelon Electric Vehicle Routing Problem with Time Windows and Battery Swapping Stations

2021 ◽  
Vol 11 (22) ◽  
pp. 10779
Author(s):  
Dan Wang ◽  
Hong Zhou
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
High Efficiency ◽  
Programming Model ◽  
Time Windows ◽  
Transportation Cost ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Fixed Cost ◽  
Routing Problem

Driven by the new laws and regulations concerning the emission of greenhouse gases, it is becoming more and more popular for enterprises to adopt cleaner energy. This research proposes a novel two-echelon vehicle routing problem consisting of mixed vehicles considering battery swapping stations, which includes one depot, multiple satellites with unilateral time windows, and customers with given demands. The fossil fuel-based internal combustion vehicles are employed in the first echelon, while the electric vehicles are used in the second echelon. A mixed integer programming model for this proposed problem is established in which the total cost, including transportation cost, handling cost, fixed cost of two kinds of vehicles, and recharging cost, is minimized. Moreover, based on the variable neighborhood search, a metaheuristic procedure is developed to solve the problem. To validate its effectiveness, extensive numerical experiments are conducted over the randomly generated instances of different sizes. The computational results show that the proposed metaheuristic can produce a good logistics scheme with high efficiency.

scholarly journals New general mixed-integer linear programming model for mobile workforce management

2021 ◽  
Author(s):  
András Éles ◽  
István Heckl ◽  
Heriberto Cabezas
Keyword(s):  
Programming Model ◽  
Time Windows ◽  
Mutual Exclusion ◽  
Parallel Execution ◽  
Mixed Integer ◽  
Management Problem ◽  
Routing Problem ◽  
Workforce Management ◽  
Computational Performance ◽  
Wide Range

AbstractA mathematical model is introduced to solve a mobile workforce management problem. In such a problem there are a number of tasks to be executed at different locations by various teams. For example, when an electricity utility company has to deal with planned system upgrades and damages caused by storms. The aim is to determine the schedule of the teams in such a way that the overall cost is minimal. The mobile workforce management problem involves scheduling. The following questions should be answered: when to perform a task, how to route vehicles—the vehicle routing problem—and the order the sites should be visited and by which teams. These problems are already complex in themselves. This paper proposes an integrated mathematical programming model formulation, which, by the assignment of its binary variables, can be easily included in heuristic algorithmic frameworks. In the problem specification, a wide range of parameters can be set. This includes absolute and expected time windows for tasks, packing and unpacking in case of team movement, resource utilization, relations between tasks such as precedence, mutual exclusion or parallel execution, and team-dependent travelling and execution times and costs. To make the model able to solve larger problems, an algorithmic framework is also implemented which can be used to find heuristic solutions in acceptable time. This latter solution method can be used as an alternative. Computational performance is examined through a series of test cases in which the most important factors are scaled.

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