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In order to improve the service level of pedestrian service system on urban arterial roads from the perspective of pedestrian perception,a pedestrian service level evaluation model is established,which takes the accessibility,safety and comfort as the first evaluation index,and street environmental factors and traffic characteristics as the second evaluation index. Taking 10 arterial roads around Xinjiekou area in Nanjing as the research object,the correlation of model parameters is analyzed by fitting index. The results show that the correlation coefficient of pedestrian walking speed,motor vehicle speed and total width of motor lane is less than 0. 3,which is in the range of no correlation or weak correlation. After deletion,the revised secondary evaluation index is obtained. Linear regression analysis is carried out on service level,first-level evaluation index and second-level evaluation index,the coefficients of each variable are obtained. The results show that the evaluation model of pedestrian service level is reasonable,which can be used to study the service level of pedestrian service system on urban arterial roads,and provide theoretical basis for relevant departments of urban non-motorized traffic to take targeted improvement measures. [ABSTRACT FROM AUTHOR]

The article deals with a mathematical model of production inventory system of green products in a green manufacturing industry. The main objective of this proposed model is to formulate a profit function for service level and random variable dependent demand implementing green technology in the manufacturing industry for reduction of green house gas emission. The production lotsize is considered here as an increasing function of green technology and capital invested for setup the manufacturing system which meets the market demand. As a result, green technology, capital invested for setup and service level are decision variable which are optimized to achieve maximum profit. Finally, numerical example for normal distribution and distribution free cases are illustrated to justify the proposed model. [ABSTRACT FROM AUTHOR]

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In this paper, by developing the Capacitated P-Median Problem (CPMP) mathematical planning model, we try to model the problem in such a way that the service to customers according to the service level is effective in the optimum solution, and to some extent, brings the CPMP closer to actual circumstances. Adding the service level will convert the CPMP from a deterministic state to a stochastic model in which demands can have any distribution function. If the customer demand follows the normal distribution function, this stochastic model can be converted to a Mixed Integer Nonlinear Programming. This obtained model is used in a real case study to develop tanks of an oil refinery so that the costs are minimized and the customer demand is met at an acceptable level. In addition, comparing the new model with the traditional CPMP Model, by solving a real case study, shows the efficiency of the proposed model. [ABSTRACT FROM AUTHOR]

The key idea of the paper is the development of a probabilistic model for optimum inventory policy for a three-product, four-echelon, distributive system. The mathematical model is built based on integer policy of ordering in the deterministic part with continuous review inventory policy. It is found to be a non-linear multi-variable constrained optimization problem. For illustration purpose, demand is taken as stationery random one and lead time is normally distributed. A MATLAB program is generated to derive the solution based on exhaustive search method. Optimum lot sizes, safety stocks, reorder points, and service levels for each product at each stage are found out in accordance with continuous review inventory system. Further inventory turnover ratio computed is found to be reasonable and bubble plot of chosen service levels of different products with annual sales, profit margin, variability in demand, and lead time is obtained with expected characteristics. The proposed model along with the applied method of solving can find the best possible order quantity and ROP of a stochastic inventory system efficiently. [ABSTRACT FROM AUTHOR]

Motivated by the importance of service quality in nowadays customer business environment, we focus on inventory optimization under probabilistic service level constraints, namely, the α service level (also known as the ready rate) or the β service level (also known as the fill rate). Under service level constraints, we consider two canonical stochastic inventory models: (i) the classical inventory control model with backlogging and (ii) the remanufacturing inventory control model with random product returns. The random demands could be non‐stationary, evolving and correlated over time. For each model, we first establish the optimality of generalized base‐stock policies, and then propose a new approximation algorithm that admits a worst‐case performance guarantee of 2. The core concept developed in this study is called the delayed forced holding and production cost, which is proven effective in dealing with service level constrained inventory systems. We also provide an efficient heuristic algorithm for the multi‐item inventory system. Our extensive computational experiments show that the proposed algorithms perform within 2% of optimality. [ABSTRACT FROM AUTHOR]

PT. XYZ has some problems in scheduling ABC product distribution, which the company has excessive stock in the main warehouse, but stockout happened in regional warehouses. Another problem is that the company has established a 90% service level for safety stock, but it is not applied in the regional warehouse. The objectives in this research are to find out the appropriate safety stock quantity so 90% service level that company established can be achieved, to know company distribution schedule, and to count the most efficient expense that company will pay. To aim these research objectives, it started by using the Bayes method to know demand forecasting, then established safety stock quantity to fulfill 90% service level, and using DRP to scheduling company distribution activity. The results from this research are knowing safety stock quantity in the warehouse so it can fulfill 90% service level, knowing distribution schedule, and the most efficient expense that the company has to pay. According to the results, the DRP method can be used to overcome company problems and fulfill their expectation that the company has established, and estimate distribution budget. [ABSTRACT FROM AUTHOR]

This study examines the impacts of three factors including service, price, and discount on the supply chain's profit. We consider a supply chain, including one traditional retailer and two manufacturers. By using the game-theoretic approach, we derived optimal solutions and analyzed competition between members under two scenarios: (1) the retailer buys the products from two manufacturers without price discount contracts, i.e. no products are sold with price discount contract. (2) The retailer buys the product from one of the manufacturers with price discount contract. We find that the price discount rate and the service level are very effective on the demand and profit of supply chain members and determining the appropriate discount rate is very important. The results show that increasing the service level provided by the retailer does not necessarily increase the profit of the manufacturer and he should set an appropriate discount rate to increase his profit. Our work contributes to three aspects: (1) joint and simultaneous examination of competition in the supply chain under the three factors of price discount, price, and service level; (2) examination of competition in the supply chain where the retailer and a manufacturer provide free service to consumers; and (3) analysis and comparison of the numerical example results in the two above scenarios according to the sensitivity analysis of various parameters. [ABSTRACT FROM AUTHOR]

ETC system used in the parking lot can effectively alleviate the traffic congestion, reduce vehicle traffic delay time and the average queue length, improve the overall lane capacity and service level. Based on the traffic flow characteristics of the parking lot, the vehicle arrival characteristics, vehicle transit process characteristics, the ETC, MTC lane capacities are analyzed. This paper presents an ETC lane capacity calculation model with MTC misappropriation rate. The M/G/K queuing theory model is used to analyze the MTC lane capacity, and the evaluation index and calculation method of parking service fee are set up. Through the actual survey of the parking lot calibration parameters and the use of Vissim simulation model, the traffic and ETC use rates in different proportions, the vehicle traffic parking lot lane average delay time are obtained. For the cases that ETC utilization rates are 30% , 50% , 70% and the traffic volume is 180 pcu/ha, optimal allocation schemes of ETC lane number are put forward, respectively, which can provide reference for the use of ETC system. [ABSTRACT FROM AUTHOR]

Nowadays, retailers sell both green and non-green products to consumers. In many real world retailing businesses, owing to shelf-space limits and to avoid cannibalization between products, retailers only sell either the green or the non-green product but not both at the same time. Then, an important question arises: Should the retailer sell the green product first or not? This question is critical in the big data era because the retailer can use advanced technologies to collect a massive amount of demand data of the product sold first and then update the demand forecast for the forthcoming product, which improves its retail business performance and services. In this paper, by constructing a Bayesian information inventory updating model, we identify the analytical conditions for the retailer to decide the optimal selling sequence. Moreover, we uncover that when the green product's service level is lower than the non-green one's, selling the green product first surely produces a lower environmental cost. However, when the green product's service level is higher than the non-green one's, selling the green product first does not always produce a lower environmental cost. Furthermore, we investigate the impact of big data on the profit improvement and the environmental cost improvement, and its relationship with the optimal selling sequence. • Discuss when retailers should sell green products first. • Using data to achieve forecast updates • Compare service levels of green and non-green products. • Reveal impacts of big data on profit and environmental cost improvements. • Report big data's relationship with the optimal selling sequence. [ABSTRACT FROM AUTHOR]

• A new stochastic IRP with partial distributional information on demands is studied. • A distributionally robust model with a probabilistic objective function is proposed. • The sample average approximation method and a hierarchical approach are proposed. This paper studies a stochastic inventory routing problem with alternative handling modules and limited capital budget, under partial distributional information (i.e., the mean and covariance matrix of customer demands). The objective is to maximize the service level, i.e., the probability of jointly ensuring no stockout and respecting the warehouse capacities for all customers at the end of each period. A novel distributionally robust chance constrained formulation is proposed. The sample average approximation method and a model-based hierarchical approach based on problem analysis are developed. Computational results show that the latter approach is more efficient. We also draw some managerial insights. [ABSTRACT FROM AUTHOR]

Stochastic inventory system simulation is often the tool of choice by industry practitioners who struggle with the evaluation of the quality of proposed inventory targets using service levels. However, driving simulations with unknown input distribution parameters has its own challenges. In this paper, we focus on the newsvendor problem and quantify the amount of demand parameter uncertainty – the uncertainty around the unknown demand distribution parameters which are estimated from the limited historical demand data – in the confidence interval of the mean service level. We use this quantification to understand how the variance of the mean service level, due to the amount of the demand parameter uncertainty in the simulation output process, changes with the choice of Type-1 and Type-2 service-level criteria, the historical data length, the ratio of the unit shortage cost to the unit holding cost, and the distributional shape of the demand's density function. [ABSTRACT FROM AUTHOR]

Nowadays, more and more transactions or interactions like online dating and shopping are completed on two-sided platforms involving two groups of agents. On these two-sided platforms, there often exist cross-network effects, i.e., the benefits that agents at one side receive are positively related to the number of agents at the other side, and vice versa. This paper considers such two-sided platforms, where the platforms offer a certain service to attract agents of both sides to join the platforms, and then charge agents who join the platforms a lump-sum fee to gain the profit. We present service and pricing strategies for both monopolistic and duopolistic platforms, respectively. We also investigate the impact of platforms' life cycle on their service and pricing strategies. Some managerial implications are shown. [ABSTRACT FROM AUTHOR]

We propose a sample-average-approximation-based simulation optimisation approach for solving a two-echelon inventory problem containing a total cost objective function and multiple service-level constraints. Some necessary parameter settings and conditions are provided to achieve the stopping condition in practice and the convergence to the optimal solution. The approach takes into account the stochastic nature of the objective and constraint performance measures, and allows the customer demands to occur with a random size and all events to occur at random points in time (including the stochastic lead times). Experimental studies are performed to evaluate the efficiency of the developed algorithms and other existing solution approaches. [ABSTRACT FROM AUTHOR]

Management of wastewater in rural areas is important for improving the sanitation services which has remained relatively neglected in India and other developing countries. This study aims to analyse the service quality of attributes of wastewater management (WWM) infrastructure and to determine their service delivery levels from local communities' perspective which is required for the sustainability of the provided facilities. The study was conducted in a few villages of the Gaya district of Bihar, India with a sample size of 1,204. Twelve attributes are identified and selected after extensive literature review, focus group discussions and experts' opinion survey, and appropriate service delivery level for each attribute is determined using level of service (LOS) scale, zone of tolerance (ZOT) and through users' satisfaction level (USL) values for each attribute. The findings reveal that while service level of most of the attributes is perceived as LOS C, the expected service level for the attributes lies between LOS A and C. The proportion of households satisfied at the upper and lower ranges of ZOT also varies from one attribute to another. The framework developed in this research would help policy makers to determine appropriate service delivery level of WWM attribute and other infrastructure in rural areas. [ABSTRACT FROM AUTHOR]

Data analysis in this study was carried out using the Importance Performance Analysis (IPA) analysis method. Importance Performance Analysis (IPA) is used to map the relationship between service (importance) and performance (performance) of each service attribute according to the assessment/perception of passengers on the Ternate – Bitung Ferry. The level of service of the Ternate-Bitung Sea transportation mode using the Importance Performance Analysis (IPA) method is obtained by variables that have high importance/expectations, but performance/reality is quite good. Services that are considered good include: Information services and Ferry Rates, Convenience of seating on the Ferry, Lighting at night, Availability of departure/arrival schedules, Appropriate/not rate rates. While the variables that are considered less important by passengers, but whose performance is good so that passengers think that the performance is excessive, namely: Strict action by officers for those who violate, Places for storing goods, Availability of compass/GPS navigation tools, Availability of life jackets/life jackets, Availability of first aid kits, Availability of radio equipment, Availability of distress signals.

The current global market situation pursues high adaptability, but why? Complexity due to mass customization is greater than ever. Globalization is no longer a theory but a fact that makes disruptions in the globalized supply chain a major risk for operations. In this context, customers demand novelty and unique experiences. These are the main drivers for market success. Therefore, existing products are now in continuous states of change with shortened product lifecycles. The purpose of this article is to analyze the impact of new market entries and product changes along the lifecycle as well as supply chain disruptions in supplier inventory levels. The goal is to minimize costs by achieving a given service level with a market-oriented procurement planning model. The model pursues minimizing the time needed to align the system with the market and, therefore, the adaptability of the system. The research compares classical inventory management models with the new proposed approach by means of simulation with the system dynamics methodology. The results show how the proposed model increased the delivery service level, reduced inventory costs, and increased the utilization of resources due to lower demand uncertainty. Therefore, the developed model is able to plan the inventory supply with a low risk of stock outages. The conclusion proposes a differentiated forecasting and inventory strategy depending on the product lifecycle stage. The developed market-oriented procurement planning model provides guidance for inventory managers regarding how to optimize their operations as an opportunity within the fourth industrial revolution to develop information technology (IT) systems to gather and utilize demand and inventory data with real-time efficiency.

The liner shipping industry plays a pivotal role in global cargo transportation, catering to both contract and spot shippers. Proper capacity allocation between these shippers is vital for maintaining service quality and improving revenue. This research investigates the service-oriented container slot allocation problem under stochastic demand, aiming to maximize total freight revenue while providing adequate service levels to contract shippers for sustaining their market loyalty. We use the fill rate (i.e., the proportion of satisfied demand) as a metric for service level and formulate the research problem as a stochastic linear programming model. To solve this model, we convert it into a multi-objective attainability problem by setting a target for total revenue, and apply Blackwell's Approachability Theorem to theoretically determine the feasibility of any given revenue and service level requirements. Leveraging these insights, we devise near-optimal policies to guide the slot allocation decision under each demand scenario. Numerical experiments demonstrate that our approach outperforms the benchmark policies in the literature. Furthermore, it can also achieve near-optimal performance closely resembling the sampling average approximation (SAA) solution while significantly reducing the computational time. • The service-oriented slot allocation problem under stochastic demand is considered. • A stochastic linear programming model with service level constraints is proposed. • An efficient solution framework for the stochastic linear programming model is designed. • One of the near-optimal solutions with high computational efficiency is achieved. • A series of numerical experiments are carried out. [ABSTRACT FROM AUTHOR]

In humanitarian logistics, the location and inventory pre-positioning problem (LIPP), making decisions on facility location, inventory pre-positioning, and allocation, is critical to post-disaster rescue efficiency. Since post-disaster conditions are complex and uncertain, it is challenging for planners to make LIPP decisions and perform rescue activities. To reduce operational costs while also guaranteeing service levels to customers, it is necessary to take uncertainties into account when making decisions. This study explores a service-oriented LIPP under two types of uncertainties, i.e., uncertain customer demand and third-party supply. We propose a two-stage robust optimization framework to solve the problem, considering the service-level constraints and minimizing the total cost. We develop two algorithms to solve the problem. Specifically, a column-and-constraint generation algorithm is utilized to solve the original two-stage robust model, and an improved row generation algorithm is developed to tackle the affinely adjustable robust counterpart model. Simulation results show that both algorithms can provide satisfying solutions. A case study based on a power grid company in China is conducted to perform sensitivity analysis and compare models, producing several managerial insights. • Study the location and inventory pre-positioning problem with uncertainties. • Consider service level and propose a two-stage robust model. • Develop column-and-constraint generation and row generation algorithms. • Conduct simulations to compare algorithms and a case study to gain insights. [ABSTRACT FROM AUTHOR]

To gain ridership, bus services need to offer more than just high frequencies. An attractive system design for Bus Rapid Transit (BRT) is a result of various configurational choices concerning infrastructure, rolling stock and operations. To find out which configurations are preferred by potential and current passengers, a Discrete Choice Experiment was carried out in The Netherlands. For this study, eight BRT characteristics were included. Results (n = 1019) show that four characteristics are valued the most: frequency, service hours, reliability and stop spacing. The attractiveness of three different service formulas or configurations is evaluated. The more conventional bus configuration is preferred by the majority of the respondents. However, a considerable amount (25%) of respondents that prefer this configuration does not consider using this service formula. Configurations that either address offering more passenger comfort or higher capacity, do seem to be attractive to distinct passenger segments who are more likely to actually use the service. These appealing BRT configurations address different types of passenger segments and therefore could coexist on certain routes. [ABSTRACT FROM AUTHOR]

There are many studies that emphasize as a first objective of inventory management to minimize the value invested in inventory because it has a direct impact on return on assets. This approach is not fully correct. The actual objective is to determine the value and the mix of inventory that support a high service level for customers and that maximizing the companies’ financial performance. Many companies look at their own demand fluctuations and assume that there are too many variables to predict demand variability. Service level is used in inventory management to measure the performance of inventory policies and represents the probability of not being stock-out and not losing sales. Safety stock is inventory that is carried to prevent stock outs. Safety stock determinations are not intended to eliminate all stock outs, just majority of them. Companies choose to keep safety stock level high as a buffer against demand variability resulting in inefficiencies and high working capital requirements. Safety stock optimization enables companies to achieve savings and increase inventory turns.