scholarly journals The Value of Inaccurate Advance Time Window Information in a Pick-Up and Delivery Problem

2014 ◽  
Author(s):  
F. Jordan Srour ◽  
Niels Agatz ◽  
Johan Oppen
Keyword(s):  
Time Window ◽  
Delivery Problem ◽  
Advance Time

scholarly journals Scheduling the periodic delivery of liquefied petroleum gas tank with time window by using artificial intelligence approaches: An example in Taiwan

2021 ◽  
Vol 104 (3_suppl) ◽  
pp. 003685042110403
Author(s):  
Yi-Chih Hsieh ◽  
Peng-Sheng You ◽  
Cheng-Sheng Chen
Keyword(s):  
Evolutionary Algorithms ◽  
Time Window ◽  
Random Sequence ◽  
Cooking Time ◽  
Liquefied Petroleum Gas ◽  
Swarm Optimization ◽  
Encoding Scheme ◽  
Delivery Problem ◽  
Long Time ◽  
Delivery Efficiency

Introduction In Taiwan, liquefied petroleum gas tank users have to call a gas company to deliver a full liquefied petroleum gas tank when their tank is out of gas. The calls usually congest in the cooking time and the customers have to wait for a long time for a full liquefied petroleum gas tank. Additionally, allocating manpower is difficult for the gas company. Objectives A strategy of periodic delivery for gas companies was presented to deliver liquefied petroleum gas tanks in advance and charge the gas fee based on the weight of returned tanks. Additionally, a new encoding scheme was proposed and embedded into three evolutionary algorithms to solve the nondeterministic polynomial-hard problem. The objective of the problem is to minimize the total traveling distance of the vehicle such that the delivery efficiency of tanks increases and the waiting time of customer decreases. Methods A new encoding scheme was presented to convert any random sequence of integers into a solution of the problem and embedded into three evolutionary algorithms, namely, immune algorithm, genetic algorithm, and particle swarm optimization, to solve the delivery problem. Additionally, the encoding scheme can be used to different frequency types of demand based on customers’ requests. Results Numerical results, including a practical example in Yunlin, Taiwan, were provided to show that the adopted approaches can significantly improve the efficiency of delivery. Conclusions The periodic delivery strategy and the new encoding scheme can effectively solve the practical problem of liquefied petroleum gas tank in Taiwan.

A Two-Phase Scheduling Method Combined to the Tabu Search for the DARP

2014 ◽  
Vol 5 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Ali Lemouari ◽  
Oualid Guemri
Keyword(s):  
Tabu Search ◽  
Time Window ◽  
Total Duration ◽  
Two Phase ◽  
Transportation Services ◽  
Delivery Problem ◽  
Pickup And Delivery Problem ◽  
Early Arrival ◽  
Scheduling Method ◽  
Transportation Applications

The dial-a-ride problem (DARP), is a variant of the pickup and delivery problem (PDP), consists of designing vehicle routes of n customers transportation requests. The problem arises in many transportation applications, like door-to-door transportation services for elderly and disabled people or in services for patients. This paper consider a static multivehicle DARP, which the objective is to minimize a combined costs of total travel distance, total duration, passengers waiting time, the excess ride time of customers, and the early arrival time while respecting maximum route duration limit, the maximum costumer ride time limit, the capacity and the time window constraint. The authors propose a two-phase scheduling method combined to the tabu search heuristic, for the static multivehicle DARP. Their experimentation report best results for Cordeau Benchmark test problem, compared to reported results.

scholarly journals Research on Coordination and Optimization of Order Allocation and Delivery Route Planning in Take-Out System

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Guofeng Sun ◽  
Zhiqiang Tian ◽  
Renhua Liu ◽  
Yun Jing ◽  
Yawen Ma
Keyword(s):  
Time Window ◽  
Route Planning ◽  
Route Optimization ◽  
Dynamic Allocation ◽  
Improved Genetic Algorithm ◽  
Time Dimension ◽  
Order Allocation ◽  
Routing Problem ◽  
Delivery Problem ◽  
Delivery Route

This paper studies the take-out route delivery problem (TRDP) with order allocation and unilateral soft time window constraints. The TRDP considers the order allocation and delivery route optimization in the delivery service process. The TRDP is a challenging version of vehicle routing problem. In order to solve this problem, this paper aims to minimize the total cost of delivery, builds an optimization model of this problem by using cumulative time, and adds time dimension in order allocation and path optimization dimensions. It can not only track the real-time location of delivery personnel but also record the delivery personnel to perform a certain task. The main algorithm is the dynamic allocation algorithm designed from the perspective of dispatch efficiency, and the subalgorithm is the improved genetic algorithm. Finally, some experiments are designed to verify the effectiveness of the established model and the designed algorithm, the order allocation and route optimization are calculated with/without the consideration of traffic jam, and the results show that the algorithm can generate better solution in each scene.

scholarly journals Genetic Algorithm for the Pick-up and Delivery Problem with Time Window by Multi-Compartment Vehicles

2021 ◽  
Vol 22 (3) ◽  
pp. 343-352
Author(s):  
Berte Ousmane ◽  
Diaby Moustapha ◽  
Coulibaly Adama
Keyword(s):  
Genetic Algorithm ◽  
Minimum Distance ◽  
Time Window ◽  
Minimum Cost ◽  
Delivery Problem ◽  
Single Compartment ◽  
Reasonable Number

Abstract In this article we focus on multi-compartment vehicles that have to pick-up goods from suppliers and deliver them to various customers. Usually these goods cannot be transported by single-compartment vehicles due to the fact that some products are harmful to others: incompatibility between products. It is therefore a question of satisfying a set of customers while respecting the constraints linked to the capacity of each vehicle compartment, each type of product and ensuring that each supplier is visited before his customer. Our work consists firstly of mathematically modelling the problem described and secondly of solving it using methods due to its complexity. In this case we use the genetic algorithm to solve the pick-up and delivery problem of goods with a time window provided by multi-compartment vehicles. Our model allows to find a minimum distance and a minimum cost in the tour carried out by a reasonable number of vehicles.

A Route Optimizing Model and Algorithm for Pickup and Delivery Problem with Time Window

2013 ◽  
Vol 321-324 ◽  
pp. 2060-2064
Author(s):  
Ting Ting Wu
Keyword(s):  
Optimization Problems ◽  
Time Window ◽  
Time Windows ◽  
Minimum Cost ◽  
Pickup And Delivery ◽  
Delivery Problem ◽  
Soft Time Windows ◽  
Routing Optimization ◽  
Optimizing Model ◽  
Vehicle Routing Optimization

Choosing in the more practical soft time Windows the logistics pickup and delivery path choice is discussed. Setting up a more comprehensive model to get the minimum cost including the distance and time. Then improving the genetic algorithm to solve the vehicle routing optimization problems better.

Microscopic Traffic Simulation Based Dispatch Modeling for Taxi Booking Service

2011 ◽  
Vol 187 ◽  
pp. 677-682 ◽  
Author(s):  
Hao Wang ◽  
Der Horng Lee ◽  
Ruey Cheu
Keyword(s):  
Traffic Simulation ◽  
Time Window ◽  
Pickup And Delivery ◽  
Shortest Path Algorithm ◽  
Microscopic Traffic Simulation ◽  
Delivery Problem ◽  
Pickup And Delivery Problem ◽  
Trip Chaining ◽  
Simulation Based ◽  
Close Proximity

This paper presents a study of taxi booking service in Singapore using a microscopic traffic simulation model embedded with a link-to-link shortest path algorithm. A novel trip-chaining strategy for taxi booking based on a customized algorithm of Pickup and Delivery Problem with Time Window (PDPTW) was proposed. The idea is to chain several bookings with demand time points which are spread out within a reasonable period of time, and with each pick-up point coinciding with or being within close proximity to the previous drop-off location. Based on the simulation results, the proposed system has the potential to improve the taxi booking service currently operating in Singapore.

scholarly journals Study on Customized Shuttle Transit Mode Responding to Spatiotemporal Inhomogeneous Demand in Super-Peak

Information ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 429
Author(s):  
Hao Zheng ◽  
Xingchen Zhang ◽  
Junhua Chen
Keyword(s):  
Waiting Time ◽  
Public Transportation ◽  
Large Scale ◽  
Time Window ◽  
Spatiotemporal Distribution ◽  
Delivery Problem ◽  
The Public ◽  
Pickup And Delivery Problem ◽  
Passenger Flows ◽  
Public Transportation System

Instantaneous mega-traffic flow has long been one of the major challenges in the management of mega-cities. It is difficult for the public transportation system to cope directly with transient mega-capacity flows, and the uneven spatiotemporal distribution of demand is the main cause. To this end, this paper proposed a customized shuttle bus transportation model based on the “boarding-transfer-alighting” framework, with the goal of minimizing operational costs and maximizing service quality to address mega-transit demand with uneven spatiotemporal distribution. The fleet application is constructed by a pickup and delivery problem with time window and transfer (PDPTWT) model, and a heuristic algorithm based on Tabu Search and ALNS is proposed to solve the large-scale computational problem. Numerical tests show that the proposed algorithm has the same accuracy as the commercial solution software, but has a higher speed. When the demand size is 10, the proposed algorithm can save 24,000 times of time. In addition, 6 reality-based cases are presented, and the results demonstrate that the designed option can save 9.93% of fleet cost, reduce 45.27% of vehicle waiting time, and 33.05% of passenger waiting time relative to other existing customized bus modes when encountering instantaneous passenger flows with time and space imbalance.

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