The vehicle routing problem (VRP) is one of the most important combinational optimization problems that has nowadays received much attention because of its real application in industrial and service problems. The VRP involves routing a fleet of vehicles, each of them visiting a set of nodes such that every node is visited by exactly one vehicle only once. So, the objective is to minimize the to...

Production scheduling is a part of operational research which relies on combinational optimization solved by discrete methods. This wide area covers different variety of problems like; vehicle routing problem, bin packing problem and job priority. In order to solve these problems, operational research applies two main principles: exact methods which provide the absolute best solution but solve ...

This paper studies the vehicle routing and scheduling problem with time windows in the pickup and delivery service for customers via vehicles. After discussing the collaborative pattern of vehicles and defining the isolated customer point, we derive the model and strategy of single-pass multiple vehicle collaborations. And then we propose a heuristic algorithm based on single-pass multiple vehi...

We have created a framework that provides a way to represent a wide range of scheduling and assignment problems across many domains. We have also created an optimizing scheduler that can, without modification, solve any problem represented using this framework. The three components of a problem representation are the metadata, the data, and the scheduling semantics. The scheduler performs the o...

Many governments worldwide have imposed hours of service regulations for truck drivers to ensure that break and rest periods are regularly taken. Transport companies have to take these into account and plan the routes and schedules of their truck drivers simultaneously. This problem is called vehicle routing and truck driver scheduling problem (VRTDSP). With their paper “An exact method for veh...

Due to the suddenness and uncertainty of COVID-19, sufficient emergency resources should be allocated appropriate space within a limited time. In order ensure smooth implementation resource scheduling, must timely effectively supplied. Therefore, it is great significance study how reasonably distribute optimize vehicle routing problem improve efficiency emergency. Based on research capacitated ...

In this paper, a survey is presented on the use of optimization models for integration electric vehicles (EVs) and charging stations (CSs) in energy system, paying particular attention both to planning problems (i.e., those related long term decisions such as siting sizing CSs), operational management optimal scheduling EVs smart grids, microgrids buildings taking into account vehicle-to-grid (...

This paper presents the development of a novel framework that optimizes the evacuation of large cities using multiple modes including vehicular traffic, rapid transit, and mass transit shuttle buses. A large-scale evacuation model is developed for the evacuation of the City of Toronto in cases of emergency. A demand estimation model is first designed to accurately quantify the evacuation demand...

Using Greedy Clustering Method to Solve Capacitated Location-Routing Problem with Fuzzy Demands Abstract In this paper, the capacitated location routing problem with fuzzy demands (CLRP_FD) is considered. In CLRP_FD, facility location problem (FLP) and vehicle routing problem (VRP) are observed simultaneously. Indeed the vehicles and the depots have a predefined capacity to serve the customerst...

centralizing and using proper transportation facilities cut down costs and traffic. hub facilities concentrate on flows to cause economic advantage of scale and multimodal transportation helps use the advantage of another transporter. a distinctive feature of this paper is proposing a new mathematical formulation for a three-stage p-hub location routing problem with simultaneous pick-ups and de...