Customer Locations Research Articles

Mathematical Models for the Vehicle Routing Problem by Considering Balancing Load and Customer Compactness

The vehicle routing problem seeking to minimize the traveled distance and the deviation of the total workload is known as the vehicle routing problem with workload balance (WBVRP). In the WBVRP, several elements are considered: (i) the total distance or driving time, (ii) the number of customers to be visited, and (iii) the total weight or amount of delivered goods. We have considered the WBVRP by adding a concept called customer compactness and the visual attractiveness of the routes. The WBVRP allows a similar workload for drivers to improve their well-being and social development. Unbalanced routes could generate high costs due to potential strikes by drivers seeking an equitable workload. We have proposed three mathematical formulations for solving the WBVRP by minimizing the customer compactness and the distance with and without considering workload balancing. The workload balancing is based on the deviation concerning the average load of the routes and considering waiting and driving time. We have tested the efficiency of the proposed models on a synthetic set of instances, analyzing different aspects such as depot location, customer location, and demand. The analysis of the results has been performed considering customer compactness and the visual attractiveness of the obtained solution. Computational experiments on generated random instances show the efficiency of the proposed approaches.

Quantitative tools for maintenance planning for in-situ service entities

The company under study is dedicated to providing in-situ maintenance services, its objective is to provide comprehensive security technical goods and services to national and foreign entities, according to current standards; with professionalism and advanced technologies, guaranteeing the primacy in the national market and promoting exports. These services involve moving employees and equipment to the physical locations of customers. The companies that are dedicated to guaranteeing Security Systems, need to always keep the equipment installed available to the clients, so it is essential for them to periodically restore the capacities of these systems. The objective of this work is to propose the use of a set of quantitative tools that allow to increase the efficiency and effectiveness in the planning of on-site maintenance services. The security and protection company under study for the application of the proposal, improved considerably in terms of availability of the systems installed to customers and in the use of the resources. The work includes tools for the planning phases: long-term, which will be carried out annually, short-term, to decide on a monthly basis which clients will be served and the daily one in which it is determined on a daily basis which clients will be served.

A Novel Green Logistics Technique for Planning Merchandise Deliveries: A Case Study

Background: The health crisis due to COVID-19 has changed the habits of social coexistence and therefore has had a significant impact on several economic sectors, including logistics. Nowadays, this sector faces one of the most difficult challenges in history and hence has carried out innovative strategies to adjust to the new normal and guarantee the permanence of the supply chain. In this paper, a novel green logistics technique for planning merchandise deliveries is introduced herein. Methods: This technique is based on a modified version of the Resistive Grid Path Planning Methodology (RGPPM) to establish a path through georeferential locations for delivering merchandise to customers. To do this, multi-connected resistive grids are based at customer locations for searching the path connecting the positions through electronic circuit analysis techniques. Results: Experimental results reveal that the proposed method can find a minimum spanning tree that connects all hand-over points by a continuous path. This finding has represented a reduction of around 45% in the length of the path with respect to the longest path. Conclusions: Finally, this technique is capable of addressing different optimization strategies, locating a merchandise distribution center and exploring environmental standards to reduce fuel consumption.

Optimising vehicle and on-foot porter routing in urban logistics

As modern cities expand, parcel carriers are obliged to deal with the various last-mile challenges of the urban setting, in order to meet the ever-increasing requirements of consumers while ensuring an eco-friendly distribution system. Some of the urban last-mile challenges, such as kerbside parking limitations and vehicle access restrictions, pose additional constraints to carriers that operate van-based deliveries. This paper describes a new distribution model and an associated optimisation problem, namely a vehicle routing problem with portering (VRP-P) with time windows, that integrates on-foot porters with cargo vans. In this distribution strategy, vans rendezvous with porters at handover points at selected customer locations where the transfer of parcels can take place, avoiding the need for designated parking spaces. The VRP-P is modelled as a mixed-integer linear programming formulation and solved on real delivery data in central London. The paper also describes a fast heuristic that uses several improvement operators. Computational results show that the use of portering yields time and carbon savings of up to 89%, depending on the number of customers served. The heuristic obtains high-quality feasible solutions in short computational times and outperforms a commercial optimiser on large scale instances. The findings also show high utilisation of portering even at limited parcel carrying capacities. • We describe an urban delivery system that integrates routing of vans and porters. • We introduce a new mixed-integer linear programming model to solve the problem. • An actual data set from London deliveries is used for analysis. • We propose an efficient heuristic which produces results in short computational time. • Portering achieves up to 50% and 89% time and carbon savings, respectively.

OPTIMIZING DISTRIBUTION ROUTE OF PACKED DRINKING WATER WITH THE CLARKE AND WRIGHT SAVINGS AND NEAREST NEIGHBOR METHODS (Case Study of PT. GSI)

In the business, distribution has a very important role. The distribution process must be able to deliver products on time while it also reduces the transportation costs which can consume around 50% of the company's total logistics costs. If distribution costs can be reduced, it can indirectly increase the company’s profit. PT. GSI, located in Yogyakarta, is a distributor of packed drinking water company with brand “PLG”. In determining the distribution route, PT. GSI does not use any scientific method and only uses the driver’s intuition. The purpose of this study is to optimize the distribution route of the “PLG” packed drinking water delivery to obtain the minimum mileage by using the Clarke and Wright Savings and Nearest Neighbor methods. The Clarke and Wright Savings method and the Nearest Neighbor method are used because the customer locations are far from each other and there are also customers whose delivery locations are centered on one delivery area, so that the calculation of distance savings is needed. Then the evaluation is done to determine which method is better. The comparison of the solution for data on 1st ,2nd ,3rd ,4th, and 6th March 2021 showed that the Nearest Neighbor method proposed best solution while data on 5th March 2021 showed that Clarke and Wright Savings giving the best solution. The results show that the Nearest Neighbor method provides better result in determining the distribution routes of PT. GSI.

ANDROID-BASED D’LAUNDRY APPLICATION USING MODEL DESIGN THINKING

Research problems felt by urban communities, the majority of whom are workers, both in government agencies, or in companies, are working 8 hours a day, unfavorable weather and returning home to rest. Especially during the COVID-19 pandemic and the PPKM (Enforce Activity Restrictions Offices in non-essential sectors) that is running, it makes people extra full to manage their time and prioritize between home and office. This busyness is the problem raised in this study. The solution offered is to a laundry delivery message application that is able to answer challenges with an excellent service model, namely pick-up and drop-off to the customer's location so that users can work quietly without having to be preoccupied with picking them up to the laundry location. gadgets on the Android operating system, administration and delivery services can be accessed more practically and are very easy to use, and other advantages can save time and costs. This application is an information system based on mobile devices which was developed with the Design Thinking model. The purpose of Design Thinking is process or method of thinking to empathize with human-centered problems, and also associated with product and Innovation service business and social

Hybrid fleet capacitated vehicle routing problem with flexible Monte–Carlo Tree search

The rise in EVs popularity, combined with reducing emissions and cutting costs, encouraged delivery companies to integrate them in their fleets. The fleet heterogeneity brings new challenges to the Capacitated Vehicle Routing Problem (CVRP). Driving range and different vehicles' capacity constraints must be considered. A cluster-first, route-second heuristic approach is proposed to maximise the number of parcels delivered. Clustering is achieved with two algorithms: a capacitated k-median algorithm that groups parcel drop-offs based on customer location and parcel weight; and a hierarchical constrained minimum weight matching clustering algorithm which considers EVs' range. This reduces the solution space in a meaningful way for the routing. The routing heuristic introduces a novel Monte–Carlo Tree Search enriched with a custom objective function, rollout policy and a tree pruning technique. Moreover, EVs are preferred overother vehicles when assigning parcels to vehicles. A Tabu Search step further optimises the solution. This two-step procedure allows problems with thousands of customers and hundreds of vehicles to be solved accomodating customised vehicle constraints. The solution quality is similar to other CVRP implementations when applied to classic VRP test-instances; and its quality is superior in real-world scenarios when constraints for EVs must be used.

RANCANGAN SISTEM MONITORING PENGIRIMAN BARANG BERBASIS WEBSITE PADA PT. DENSO CENTRA

The purpose of this research is to design a delivery information system for Denso Centra company. PT. Denso Centra is a company engaged in the sale of auto spare parts. In the delivery process to the customer's location, couriers often forget the customer's location and in reporting shipments there are often queues. Based on the analysis using the PIECES framework, it can be concluded that the main problem of PT. Denso Centa is the accuracy and efficiency of information that is less than the maximum on the running system so by making this web-based system it is hoped that it can produce better information. With the design of a website-based application program at PT. Denso Centra, is expected to help simplify the management of data on the delivery of goods and speed up the process of making reports to the leadership. The results of the modeling are in the form of use case diagrams, class diagrams, activity diagrams, and sequence diagrams. While the software used is the PHP and MySql Web programming languages and Micro Dreamweaver. The results of the research are in the form of a web-based delivery system which is expected to overcome the problems that exist in the delivery of goods at PT Denso Centra

Branch-Cut-and-Price for the Time-Dependent Green Vehicle Routing Problem with Time Windows

Motivated by rising concerns regarding global warming and traffic congestion effects, we study the time-dependent green vehicle routing problem with time windows (TDGVRPTW), aiming to minimize carbon emissions. The TDGVRPTW is a variant of the time-dependent vehicle routing problem (TDVRP) in which, in addition to the time window constraints, the minimization of carbon emissions requires determination of the optimal departure times for vehicles, from both the depot and customer location(s). Accordingly, the first exact method based on a branch-cut-and-price (BCP) algorithm is proposed for solving the TDGVRPTW. We introduce the notation of a time-dependent (TD) arc and describe how to identify the nondominated TD arcs in terms of arc departure times. In this way, we reduce infinitely many TD arcs to a finite set of nondominated TD arcs. We design a state-of-the-art BCP algorithm for the TDGVRPTW with labeling and limited memory subset row cuts, together with effective dominance rules for eliminating dominated TD arcs. The exact method is tested on a set of test instances derived from benchmark instances proposed in the literature. The results show the effectiveness of the proposed exact method in solving TDGVRPTW instances involving up to 100 customers. Summary of Contribution: Due to the environmental situation, green vehicle routing problems (GVRPs) aim to consider greenhouse gas emissions reduction, while routing the vehicles, and play a key role in transportation and logistics. Vehicle greenhouse gas emissions strongly depend on the vehicle speeds and traffic conditions which in real life vary continuously over time. To tackle these challenges, we address the time-dependent green vehicle routing problem with time windows (TDGVRPTW) aimed at reducing total carbon emissions under time-dependent travel times and time window constraints. We design an effective exact method for the TDGVRPTW based on a state-of-the-art branch-cut-and-price algorithm. The paper is both of methodological value for researchers and of interest for practitioners. For researchers, the presented algorithm is amenable for various routing constraints and provides a ground for further studies and research. For practitioners, the paper suggests insights on how the carbon emissions change based on different vehicle speed profiles. History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms—Discrete. Funding: This research is supported by the National Natural Science Foundation of China [Grants 71831003, 71831006, 72171043, and 71901180] and the Fundamental Research Funds for the Central Universities [Grants N170405005 and N180704015]. Supplemental Material: The electronic companion is available at https://doi.org/10.1287/ijoc.2022.1195 .

The vehicle sharing and task allocation problem: MILP formulation and a heuristic solution approach

In many customer service operations, workers visit customer locations to perform on-site service tasks. Each worker drives a vehicle and so the task allocation problem is often solved as a vehicle routing problem. However, unlike delivery services, the workers spend the majority of their time working on the service tasks leaving the vehicles idle. This creates a possibility of sharing vehicles among the workers to save vehicles used and reduce the total carbon emissions. This paper studies this new problem of vehicle sharing and task allocation. Given the team of workers and a set of customer tasks with their locations and time requirements, decisions need to be made on the scheduling of workers to tasks, workers sharing each vehicle and the routing of the vehicles. We first formulate the problem as an integer programming model. To solve larger problem instances, a three-phase heuristic algorithm is then developed. Computational experiments are carried out to demonstrate the benefits of sharing vehicles. The effects of problem parameters on the solution are also investigated.

Model Rute Perjalanan Minimal Dengan Menggunakan Vehicle Routing Problem Pada PT X

In this research discusses the problem of distributing goods from a depot to several customer locations to minimize travel costs. The problem is solved by using the Vehicle Routing Problem method. The data used in this research is secondary data with 10 customers and one depot. The aim of this research is to form a model from the data that has been obtained and determine the optimal travel route based on the model that has been formed. The first step is to form the objective function of the problem, then form the constraints that may occur. After the model is formed, a solution to the problem is sought. The total cost of the trip is obtained by multiplying the cost of the trip per kilometer by the total distance traveled.

Collaborative traveling salesman problem with ground vehicle as a charger for unmanned aerial vehicle

ABSTRACT Innovation in logistics industry is now implicit, and the use of unmanned aerial vehicles is at the center of logistics innovation. To effectively utilize unmanned aerial vehicles for last-mile delivery, collaborative delivery using ground vehicles and unmanned aerial vehicles has recently been investigated. However, previous studies neglected proper management of batteries, assuming their constant replacement whenever unmanned aerial vehicles land, and hence numerous batteries are required for unmanned aerial vehicles. Given this research gap, we present a new routing model for collaborative delivery wherein an unmanned aerial vehicle uses a ground vehicle as a power source. A mathematical formulation is presented, and noticing the complexity, a heuristic algorithm is developed. We present a case study to verify the operational efficiency of the model. We test the performance of the heuristic and draw insights based on geographical locations of customers via computational experiments.

Collaborative truck multi-drone routing and scheduling problem: Package delivery with flexible launch and recovery sites

This paper deals with the problem of coordinating a truck and multiple heterogeneous unmanned aerial vehicles (UAVs or drones) for last-mile package deliveries. Existing literature on truck–drone tandems predominantly restricts the UAV launch and recovery operations (LARO) to customer locations. Such a constrained setting may not be able to fully exploit the capability of drones. Moreover, this assumption may not accurately reflect the actual delivery operations. In this research, we address these gaps and introduce a new variant of truck–drone tandem that allows the truck to stop at non-customer locations (referred to as flexible sites) for drone LARO. The proposed variant also accounts for three key decisions — (i) assignment of each customer location to a vehicle, (ii) routing of truck and UAVs, and (iii) scheduling drone LARO and truck operator activities at each stop, which are always not simultaneously considered in the literature. A mixed integer linear programming model is formulated to jointly optimize the three decisions with the objective of minimizing the delivery completion time (or makespan). To handle large problem instances, we develop an optimization-enabled two-phase search algorithm by hybridizing simulated annealing and variable neighborhood search. Numerical analysis demonstrates substantial improvement in delivery efficiency of using flexible sites for LARO as opposed to the existing approach of restricting truck stop locations. Finally, several insights on drone utilization and flexible site selection are provided based on our findings.

그룹탐색최적화를 적용한 트럭-드론 스케줄링

In parallel drone scheduling traveler salesman problem, the customer can be served by a single truck or by a fleet of one or more identical drones to minimize the completion time. The vehicle routes customer locations, while the drone fly back and forth between depot and customers. The objective of this paper is to propose novel Routing Group Search Optimization (RGSO) for truck-drone scheduling to find the best schedule and routing of a truck and a droneto better balance vehicle and drone delivery. The RGSO based on Group Search Optimization (GSO) is proposed for truck-drone system with scheduling solution representation. Our proposed RGSO is very effective in finding group which are generated by relative distances of customer locations for routing of truck. Our simulation results show that RGSO is very effective comparing to standard GSO based on the several experiments and analysis.

Brand-management in the hotel industry

The article describes the benefits of using branding as a promotion tool that allows hotels to take advantage of the opportunities offered by business alliances, pricing structures, or product line expansion. The importance of brand awareness, loyalty programs for the development of the competitiveness of the campaign and obtaining the location of future customers is also substantiated.

Robust traveling salesman problem with drone: balancing risk and makespan in contactless delivery

AbstractThe spread of COVID‐19 outbreak has promoted truck‐drone delivery from trials to commercial applications in end‐to‐end contactless solutions. To fully integrate truck‐drone delivery in contactless solutions, we introduce the robust traveling salesman problem with a drone, in which a drone makes deliveries and returns to the truck that is moving on its route under uncertainty. The challenge is to find, for each customer location in truck‐drone routing, an assignment to minimize the expected makespan. Apart from the complexity of this problem, the risk of synchronization failure associated with uncertain travel time should be also considered. The problem is first formulated as a robust model, and a novel efficient frontier heuristic is proposed to solve this model. By coupling the implicit adaptive weighting with epsilon‐constraint methods, the heuristic generates a series of scalarized single‐objective problems, where the goal is to minimize expected makespan under the constraint of synchronization risk. The experiment results show that the robust (near‐)optimal solutions offer a considerable reduction in risk, yet only hint at a small increase in makespan. The heuristic in the present study is effective to construct approximations of Pareto frontier and allows for assignment decisions in a priori or a posteriori manner.

Operations design for high-velocity intra-city package service

This paper presents a network design problem in the context of intra-city courier service in megacities. The considered setting is inspired by the activities of one of the main courier package companies in China. The problem consists of designing a robust yet cost-effective service network to move packages from their origins to their destinations taking into account the committed service levels. The operational network includes two layers; the first layer consists of the network of riders, transporting packages from (to) customer locations to (from) a series of hubs, while the second layer consists of a fleet of shuttles responsible for the inter-hub transfers. In this study, we focus on shuttle activities and develop optimization technology for the design of shuttle services using novel rate-based models to determine packages as well as vehicle routes. To ensure operational simplicity, we build repeatable vehicle routes taking the form of cycles that are executed throughout the day, taking into account capacity and timing requirements. A computational study using data from a large Chinese package company shows that our technology produces a cost-effective service network design for shuttle schedules with excellent on-time performance.

Mitigation of Reactive Power and Harmonics in a Case of Industrial Customer

In most industrial plants, power quality is a major issue which hinders productivity and efficiency of the plants due to the use of semiconductor based loads and non-linear loads. As a result, to address the power quality problems in these industries, specialized power devices such as the Unified Power Quality Conditioner (UPQC), can be installed at the customer's location to resolve practically all power quality issues. UPQC consist of a series of active power filters (APF) which mitigate voltage quality issues and shunt active power filters which are used to reduce current quality issues, like harmonics and reactive power burdens. This paper, therefore presents an investigation and assessment of the power quality problems associated with Bahir Dar Textile Share Company. This was achieved by examining the voltage and current harmonic levels of various types of loads using PI and fuzzy logic controllers by measuring the level of total harmonic distortion (THD) with and without the insertion of the UPQC. The novelty of this paper is the implementation of the controller based customized UPQC for power factor and reactive power compensation. It was observed that by designing the system without and with UPQC, the results of the FFT analysis show that the fuzzy logic controller (FLC) reduced the harmonics level of the load voltage and current by 1.10% and 2.14% respectively. Generally, harmonics was alleviated by 90%, reactive power was reduced by 20%, and power factor was improved by 33%. Hence, the proposed UPQC is capable of holding the voltage and current harmonics levels within the acceptable limit, which satisfies the standards imposed by IEEE 519-1995.

Production routing for perishable products

This paper introduces the production routing problem for perishable products with fixed shelf life and gradual decay, where the age of products impacts the price that can be obtained when satisfying customer demands. In this problem, a single supplier is responsible for the production and distribution of perishable products to a set of customers. Fixed setup and variable production costs occur at the supplier location when production takes place, and routing costs are charged for the distribution activities. Additionally, inventory holding costs are incurred at both the production facility and the customer locations. Transshipments between customer locations are allowed on the basis of a unit transshipment cost. The objective is to maximise the total profit given by the sales revenue minus the sum of production, routing, inventory and transshipment costs. The problem is formulated as a mixed integer linear program and solved using a branch-and-cut and a hybrid, iterated local search-based heuristic. Based on the results of the computational experiments, we analyse the impact of perishability on the structure of the solutions. We explore perishability in the form of both product shelf life and decay, observing that larger decay rates lead to a reduction in total profit, as a result of both a decrease in revenues and an increase in the total cost. We further analyse the impact of different decay rates on the cost structure of the problem and the significance of transshipments for the management of perishability across the system. Finally, we adapt our hybrid method to solve the standard production routing problem. Comparison of our results with state-of-the-art solution methods on benchmark instances from the literature shows that our heuristic provides good quality solutions that are competitive with the scientific literature.

Drone routing problem model for last-mile delivery using the public transportation capacity as moving charging stations

The fast and cost-efficient delivery of goods ordered online is logistically a challenging problem. Many firms are looking for ways to cut delivery times and costs by exploring opportunities to take advantage of drone technology. Deploying drones as a promising technology is more efficient from both environmental and economic perspectives in last-mile delivery. This paper considers a last-mile delivery system in which a set of drones are operated in coordination with public transportation system to deliver a set of orders to customer locations. A mathematical model based on Vehicle routing Problem (VRP) is extended to solve this problem. A real-world case inspired by Bremen 2025 transportation paradigm is also developed to validate the developed mathematical formulation. Results show that the sequence of visiting customers and public transport stations highly impacts the remaining charge and efficiency of drone tour planning. Also, using public transport vehicles, which enables drones to charge their battery or to approach customers, can reduce the number of drones required for satisfying the demands in a service area. The results show that there are high potentials to save energy for drone-enabled last-mile delivery by using the public transportation network.