Improve Service Levels Research Articles

A hybrid metaheuristic approach for solving a bi-objective capacitated electric vehicle routing problem with time windows and partial recharging

PurposeThe vehicle routing problem (VRP) has been widely investigated during last decades to reduce logistics costs and improve service level. In addition, many researchers have realized the importance of green logistic system design in decreasing environmental pollution and achieving sustainable development.Design/methodology/approachIn this paper, a bi-objective mathematical model is developed for the capacitated electric VRP with time windows and partial recharge. The first objective deals with minimizing the route to reduce the costs related to vehicles, while the second objective minimizes the delay of arrival vehicles to depots based on the soft time window. A hybrid metaheuristic algorithm including non-dominated sorting genetic algorithm (NSGA-II) and teaching-learning-based optimization (TLBO), called NSGA-II-TLBO, is proposed for solving this problem. The Taguchi method is used to adjust the parameters of algorithms. Several numerical instances in different sizes are solved and the performance of the proposed algorithm is compared to NSGA-II and multi-objective simulated annealing (MOSA) as two well-known algorithms based on the five indexes including time, mean ideal distance (MID), diversity, spacing and the Rate of Achievement to two objectives Simultaneously (RAS).FindingsThe results demonstrate that the hybrid algorithm outperforms terms of spacing and RAS indexes with p-value <0.04. However, MOSA and NSGA-II algorithms have better performance in terms of central processing unit (CPU) time index. In addition, there is no meaningful difference between the algorithms in terms of MID and diversity indexes. Finally, the impacts of changing the parameters of the model on the results are investigated by performing sensitivity analysis.Originality/valueIn this research, an environment-friendly transportation system is addressed by presenting a bi-objective mathematical model for the routing problem of an electric capacitated vehicle considering the time windows with the possibility of recharging.

Towards Sustainable Transportation: A Review of Fuzzy Decision Systems and Supply Chain Serviceability

Modern requirements dictate the need for sustainable transportation systems, given the substantial growth in transportation activities over recent years that is predicted to persist. This surge in transportation has brought about environmental concerns such as air pollution and noise. To deal with this crisis, municipal administrations are investing in sustainable, reliable, economical, and environmentally friendly transportation systems. This review examines the latest developments in fuzzy decision systems for sustainable transport supplements. By reviewing the literature, we assess the serviceability of the entire supply chain to maintain transport quality, remove degradation, and meet customer demands. The link between fuzzy decision systems and supply chain serviceability may not be immediately obvious, but there are many reasons why putting them together can be a valuable focus for companies. By leveraging the capabilities of fuzzy decision systems to optimize supply chain processes and improve service levels, companies can gain a competitive advantage and better meet customer demand.

Spatial characteristics and coupling coordination between carbon emission efficiency and industrial structure in three metropolitan areas of Jiangsu Province, China.

It is of great practical significance to study the spatial characteristics of carbon emission efficiency, industrial structure, their coupling and coordination relationship for China's green development and industrial structure transformation in the new era. From the perspective of coupling, coordination and space, this paper analyzes and summarizes the spatial characteristics of carbon emission efficiency and industrial structure of 19 cities in three metropolitan areas of Jiangsu Province during 2009-2019 and their coupling and coordination relationship. The carbon emission efficiency in this study is represented by the carbon emission economic efficiency index and carbon emission social efficiency index. The results show that (a) the high-emission centers in the three metropolitan areas developed from "three centers" in 2009 to "five centers" in 2019. The continuous high-energy consumption of the secondary industry and the growth of the economic aggregate of the third industry kept the regional high carbon dioxide emissions. (b) The average value of carbon emission economic efficiency in 19 cities continued to increase, indicating that the contribution rate of the same amount of carbon emissions to economic income gradually increased; the growth range of carbon emission economic efficiency index is greater than that of carbon emission social efficiency index, indicating that carbon emission has a more significant effect on the improvement of regional economic development than on the improvement of public service level and residents' living quality. (d) The solidification degree of carbon emission efficiency is greater than that of the industrial structure (solidification degree carbon emission social efficiency > carbon emission economic efficiency > industrial structure). The high-grade industrial structure in Xuzhou metropolitan area is closely related to the improvement of carbon emission economic efficiency and carbon emission social efficiency, and both are in moderate antagonism. The rationalizing industrial structure in Nanjing metropolitan area is closely related to the improvement of carbon emission economic efficiency, which is in high coordination run-in. The concentration degree of industrial structure in Suzhou-Wuxi-Changzhou metropolitan area is closely related to the improvement of carbon emission economic efficiency and carbon emission social efficiency, which are in polar coordination coupling and high coordination run-in, respectively. The proposed coupling path of carbon emission efficiency-industrial structure can not only alleviate the dynamic disharmony in different cities but also effectively improve the coupling degree in cities.

Pricing Decision Models of Manufacturer-Led Dual-Channel Supply Chain with Free-Rider Problem

We study the strategic pricing decision models of manufacture-led dual-channel supply chains with the free-rider problem under the service level and cost. We use the Stackelberg model to study the impact of the degree with the free-rider problem of consumers on the optimal pricing strategy and the optimal service level of the dual-channel supply chain under various decision-making modes and carry out a numerical simulation. The main conclusions are as follows: In the retailer’s dual-channel supply chain, the deepening of consumer free-riding behavior will reduce the enthusiasm of retailers, but the weak position of the channel will lead to improved service levels and reduced prices, as well as to increase the wholesale price to cover costs. In the manufacturer’s dual-channel supply chain, the deepening of consumer free-riding behavior will lead to a decline in the retailers’ service level and enthusiasm, as well as to a decrease in the wholesale prices and retailers’ pricing. In the two types of dual-channel supply chains, the demand of manufacturers’ network channels increases, the price increases first and then decreases, and the profits of all supply chain members decrease with the increase in the free-rider coefficient of consumers. Finally, we use numerical simulation to verify the validity of the above conclusions, which provides a scientific basis to make optimal pricing decisions in the manufacturer-led dual-channel supply chain.

Mobile Money Operations: Policies for Managing Cash and Digital Currency Inventories in the Developing World

Problem definition: Mobile money systems—platforms built and managed by mobile network platform operators (MMPOs) to allow money to be stored as digital currency—connect millions of poor and “unbanked” people to the formal financial system. Unfortunately, low service levels because of the suboptimal management of cash and digital currency (e-float) inventory impede the development of these ecosystems. Accordingly, we seek to answer the question of how agents should manage inventories of cash and e-float. Academic/practical relevance: This paper extends inventory theory to the mobile money context, unique in that sales of cash generate inventory of e-float and vice versa. In doing so, we address a key pain point for an emerging sector that improves lives at the base of the pyramid. Methodology: We develop an analytical heuristic to determine initial stocking levels for cash and e-float and analyze its performance on simulated and actual data. Results: By partnering with an MMPO, we tested the performance of the heuristic inventory policy with data from more than 35 million transactions. The heuristic captured 99.9998% of the optimal profit on simulated data and, on actual data, we found that following the recommendations could increase agents’ profits by an average of 15.4%. Managerial implications: We develop a pragmatic inventory policy that performs nearly optimally. We also analyze under which conditions the performance deteriorates and examine heterogeneity among agents with respect to the heuristic’s impact on their performance. Thus, we equip MMPOs with guidance as to whom to target and how. By contributing to service level and profit improvements, this work can make mobile money a more effective financial inclusion tool in the developing world as well as improve the livelihoods of agents. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.1175 .

An effective disaster recovery model in supply chain management at times of pandemic

An automated model representing communicating states for a given moment in actual time is theorized in an Automated Supply Chain Dual (SC). When handling instability threats in SCs, we look at the circumstances surrounding the architecture and deployment of the digital twins. Combining models with data-driven methods show interrelationships between data risk, modeling disturbances, and performance evaluation. Digital network networking maps are distinctly visually illustrated by the SC blow and modifications amidst the COVID-19 pandemic, along with the after-event recovery method. The findings of this research complement SC risk management’s science and experience by enriching forecasting and corrective findings to exploit the merits of SC modeling, quantitative predictive data, and evidence of disruptions in real-time. The supply chains have been severely impacted by the recent coronavirus pandemic, known as the COVID-19 outbreak. Due to supply failure, demand for certain items has increased significantly, while raw materials supply required to produce those items has decreased; therefore, to address these issues, this paper proposes some strategies for improving service levels for the most sought-after products, such as toilet paper, during a severe pandemic, such as COVID-19.

Analysis of Warehouse Value-Added Services Using Pareto as a Quality Tool: A Case Study of Third-Party Logistics Service Provider

The study aims to analyse warehouse value-added services (VAS) data for a third-party logistics (3PL) service provider, which leads to identifying service improvements and cost-cutting opportunities in performing VAS for clients using Pareto analysis as a quality tool. Using a case study approach, qualitative and quantitative data were collected from a leading 3PL firm in Belgium. The approach is conducted by applying major steps of Pareto analysis. Two pharmaceutical products were analysed according to medical general classification, namely narcotic analgesics (NA) and ophthalmic antihistamines and decongestants (OAD). The results showed that the Pareto principle is proven in the NA—ticketing case, and five activities consumed 83.3 percent of the total time of VAS operations. Furthermore, in the OAD—display case, the Pareto principle is proven and six activities were validated as they accounted for 81.26 percent of the total time of primary VAS operations. The study recommended a solution to each of the four causes of delay, including lack of training/best practices, inefficient space utilization, lack of automation, and lack of cohesiveness and planning. Despite the recognized importance of avoiding warehouse operation inefficiencies, the literature lacks studies applied to practice, and few contributions exist regarding analysing 3PL service providers’ warehousing VAS operations data. This study identified all VAS activities for temperature-controlled pharmaceutical products. Moreover, the study proposes a warehouse operations improvement framework for non-automated 3PL warehouses and guides managers through Pareto analysis to cut costs and improve service level.

AGV-Based Vehicle Transportation in Automated Container Terminals: A Survey

To respond to the rapid growth of shipping container throughput, terminals urgently need to improve the efficiency of thier operations and reduce operational costs through automation and intellectualization upgrades, thereby improving service levels and enhancing market competitiveness. Due to the advantages of reliable transportation, efficient operation, and environmental friendliness, AGV-based automated container terminal (ACT) has become the development trend of container terminals. To help ACT improve its operational management capabilities, plenty of scholars have explored the transportation system of ACT. Through the analysis of operational management issues, the paper defines the four main research topics in vehicle transportation of the ACT including equipment scheduling, path planning, exception handling, and vehicle management. Then, in each topic, the works in the recent 25 years are summarized and several research opportunities for possible follow-up research directions in different fields are proposed. We expect our survey could not only provide references for more scholars on the research of operation and management of terminals, but also provide guidance for system evaluation and improvement for terminal system engineers and operation managers.

INVENTORY MANAGEMENT WITH STOCHASTIC DEMAND: CASE STUDY OF A MEDICAL EQUIPMENT COMPANY

This research proposes an inventory management system based on a periodic review model for a medical equipment company. The work aims to reduce inventory volume and out-of-stock and to improve service levels. The proposed methodology is a combined ABC/XYZ classification using the patterns and magnitude of demand under the constraints of spare parts cost. For the ABC/XYZ classification, we propose a model to forecast demand; and we evaluate eight forecasting methods to adjust the classification characteristics. The results obtained allow the reduction of arrears, an increased service level, and a decrease in average inventory.

Pricing Decision Models of the Dual Channel Supply Chain with Service Level and Return

The interests of upstream, midstream, downstream companies and consumers in the supply chain are jointly affected by service levels and returns. Improving service levels can increase market demand and improve market position, as well as reduce return rates. But the increase in service level will bring an increase in service cost. How to balance the service cost and return cost through pricing decision, so that the profit of supply chain members can be improved, is the problem studied in this paper. In this paper, we consider the effect of service level of network channel on consumers’ return behavior in the context of manufacturer’s dual-channel supply chain when dual channels provide services at the same time, and discuss the effect of service level and return rate on pricing decision of dual-channel supply chain. It was found that return behavior can stimulate manufacturers to improve service levels and increase overall supply chain profits. The higher the return rate in the network channel, the greater the benefits from improved service levels by the manufacturer and the less detrimental to retailers’ returns. This study enriches the research on pricing decisions in dual-channel supply chains, increases the motivation of merchants to improve service levels, and has some guiding implications for supply chain members to develop price and service strategies.

Aplikasi Manajemen Komplain Gedung Plaza Setiabudi Menggunakan Framework Ionic

PT Jakarta Setiabudi Internasional Tbk manages an office building located in South Jakarta, namely the Plaza Setiabudi building, with a total area of ​​22,264 m2 that can be rented and while maintaining performance and improving service levels to maintain the loyalty of building tenants. In services to building tenants, there are complaints, so that several departments involved in handling tenant complaints include Facility Management, Tenant Relations, Engineering, House Keeping, Security, and Parking. complaints to find out the process, so that customers do not need to meet employees directly and the building tenant complaint management process can be completed, the building tenant compliance management application is designed using UML (Unified Modeling Lagunage) to help describe business processes and in making applications using the Java and C# programming languages and to optimize the database using the ionic framework.

Controllable Energy Consumption in a Sustainable Smart Manufacturing Model Considering Superior Service, Flexible Demand, and Partial Outsourcing

The waste of energy in the present era is a dangerous signal for the future. All categories of consumers should come forward to moderate energy use and prevent wastage. This study focuses on a controllable energy consumption-based sustainable inventory model incorporating variable production rates, improved service, partial outsourcing planning, defective production, restoring reworkable items, disposing of non-reworkable items, and energy-saving steps. Reducing unusual energy consumption in production systems reduces carbon emissions and maximizes the system’s profit. An improved service level attracts customers, increases demand, and improves product reputation. Separate holding costs of reworked, defective, and perfect-quality items are considered for every lot delivered and reworked. The demand in the market is related to price and service. A traditional optimization technique examines the global optimization for the profit function and decision variables. Numerical illustrations as well as concave 3D graphs validate the analytical results and provide a sensitivity analysis for different parameters. The model is validated through special cases and comparison graphs.

Pilot Implementation of Innovative Proposal for Service Level Improvement in a Spare Parts Trading Company

In the context in which spare parts trading companies are becoming increasingly competitive, the level of service is essential to be able to compete in the market. This indicator is affected by on-time deliveries, which are a key factor in meeting customer demand, as this determines customer satisfaction and thus has an effect on the company's profitability. For a company to deliver its products on time, the warehouse processes must work efficiently, making the picking process one of the most critical of them. It must also run a proper inventory procurement process in order to have stock on hand to fulfill customer orders. This case study focuses on increasing the level of service in a company that sells spare parts for mining, which was found to have a low service level of 66.1%, in contrast to the recommended level for the sector, which is 85.9%. Therefore, the implementation of the 5S methodology, Systematic layout planning, demand forecasting, and cycle counting are proposed as tools to solve the root causes of the problem. The main results indicated a reduction in picking times of 36.70%, an increase in demand forecast accuracy of 13.45%, and an increase in Inventory Record Accuracy (IRA) of 5.42%.

The impact of medical service on the return behavior: A city-level study in China.

Due to the constraints of the rural-urban household registration systems, the migrants of China currently receive varying degrees of medical services. The fact that many migrants choose to return to their hometowns due to the inequality in medical care has been a social phenomenon. Using data from the 2017 China Migrant Dynamic Survey (CMDS), this paper explores the effect of medical services on population migration. Probit regression analysis method was utilized to examine the relationship between medical service level (MSL) and medical service improvement (MSI) and return behavior (RB), as well as the interaction effect between MSL and MSI, and the moderating effect of health status (HS) and health education (HE). Multiple heterogeneity tests were performed. Grouping regressions were conducted using rural household registration (RHR), grouping regressions were conducted using new rural cooperative medical system (NRCMS), and multinomial Probit regressions were conducted using migration distance and age factors. The following findings were obtained. First, when MSL is low but MSI is high in the locality of household registration, the return probability of migrants will increase. MSL also has a positive interaction effect with MSI, and they jointly increase the return probability of migrants; Second, HS and HE have a positive moderating effect on the relationships between MSL and RB and between MSI and RB; Third, heterogeneity analysis indicates that the migrants with RHR or the migrants not covered by the NRCMS are more prone to return due to the reason of medical service. In addition, the analysis also shows that middle-aged and older people who return across provinces have the highest tendency to return due to medical services and young people have the lowest propensity to return across and within provinces. The study could help local governments change their public medical care policies and close the gap between medical services in different areas. As a result, it is necessary to understand population migration trends and promote New Urbanization Strategies.

Evaluating Transit Subsidies in Chicago

This paper presents a model that calculates the social welfare benefits of using additional subsidy to reduce fare levels or improve service levels of public transit in Chicago. The model differentiates between the effects in peak and off-peak periods for both bus and rapid rail service. Results of the analysis are that bus fares should be reduced during the off-peak; rail fares are broadly acceptable; bus service levels are broadly acceptable, except for the peak period where they are too high; and rail service levels are too high at all times of the week, but especially in the peaks and on Sundays. In general, it is more advantageous to use subsidy monies to reduce fares than improve service levels. Even if overall subsidy levels were not increased, society would be better off if service levels were reduced, and the money saved channeled into reductions in fares.

A Layer-Based Relaxation Approach for Service Network Design

Service-network design in transportation applications has attracted much scientific attention due to the rapid growth of online shopping. Practical service-network planning tools could help express service providers in minimizing the total cost while improving service levels. Efficient service network design is a requirement for sustainable logistical development. Express delivery has substantial negative environmental impacts, and service network design minimizes the environmental impact by reducing energy consumption costs. This paper addresses the service network design problem, which integrates a heterogeneous fleet of vehicles for vehicle dispatching in a consolidation-based time–space network to reflect the express service scenarios. Due to the NP-hard nature of this problem, we designed a layer-based relaxation algorithm to solve large-scale applications. The relaxation method relaxes and fixes the network structure on a layer-by-layer basis, and the computational experience confirms the effectiveness and efficiency of the relaxation algorithm. The solution time and quality are both improved significantly.

Using GPS Technology to Measure On-Time Running of Scheduled Bus Services

Assessing bus service running times has been a difficult and expensive task for many urban bus operators. This has restricted the ability of operators to collect adequate data to identify problems and improve service levels. Passive Global Positioning System (GPS) devices offer a low-cost means of collecting large amounts of highly accurate data, to be used in an ongoing performance assessment program. Some programming skills are required to break continuous GPS data into information that is meaningful to a scheduler. This article provides an overview of a software application developed to process and analyze GPS datasets collected by a bus operator in Sydney, Australia, in 2002-2003. The data collection procedure and processing algorithms are described, and examples are presented of output produced by the software. The algorithm developed to process the GPS data worked well. We conclude that passive GPS is a cost-effective method of collecting data on performance. For operators running buses on five or more routes, system development costs could be recovered within two to three years.

Is the Australian primary healthcare system ready for the Rheumatic Heart Disease Endgame strategy? Data synthesis and recommendations

Is the Australian primary healthcare system ready for the Rheumatic Heart Disease Endgame strategy? Data synthesis and recommendations

RNN‐EdgeQL: An auto‐scaling and placement approach for SFC

SummaryThis paper proposes a prediction‐based scaling and placement of service function chains (SFCs) to improve service level agreement (SLA) and reduce operation cost. We used a variant of recurrent neural network (RNN) called gated recurrent unit (GRU) for resource demand prediction. Then, considering these predictions, we built an intuitive scale in/out algorithm. We also developed an algorithm that applies Q‐Learning on Edge computing environment (EdgeQL) to place these scaled‐out VNFs in appropriate locations. The integrated algorithm that combines prediction, scaling, and placement are called RNN‐EdgeQL. RNN‐EdgeQL (v2) is further improved to achieve application agnostic group level elasticity in the chain, independent of applications installed on the VNFs. We tested our algorithm on two realistic temporal dynamic load models including Internet traffic (Abilene) and an application specific traffic (Wiki) on an OpenStack testbed. The contribution of this article is threefold. First, prediction model prepares the target SFC for the upcoming load. Second, an application agnostic characteristics of the algorithm achieves the group‐level elasticity in SFC. Finally, the EdgeQL placement model minimizes the end‐to‐end path of an SFC in multi‐access edge computing (MEC) environment. As a result, RNN‐EdgeQL (v2) gives the lowest overall latency, lowest SLA violations, and lowest VNFs requirement, compared to RNN‐EdgeQL (v1) and Threshold‐Openstack default placement.

Green financing strategies in a low-carbon e-commerce supply chain under service quality regulation.

Green financing is an effective means to encourage small and medium-sized enterprises (SMEs) to improve environmental efficiency in their operations. This paper studies two financing strategies of a carbon-dependent manufacturer in an e-commerce supply chain, which are called bank credit and cost-sharing with third-party platform that provides a marketplace. The optimal carbon emission reduction (CER) level, selling price, and service level are investigated. It turns out that the participants’ profits and environmental benefit under two financing strategies are higher than those without financing. In addition, when the commission provided by the platform is low, the manufacturer is more inclined to bank credit, and when the commission is high, it is more sensible to share CER cost with the platform. The impact of government service supervision policies on corporate decision-making is further explored. The results prove that setting an appropriate service threshold and reward-penalty factor is not only conducive to incentivizing the platform to improve service level but also beneficial to the environment and overall social welfare. This paper provides cooperation strategies for manufacturers in green financing in the e-commerce supply chain and provides policy recommendations for the government to implement e-commerce service regulation and promote CER.