Delivery Time Requirements Research Articles

Energy-Efficient Algorithm for Data Path Selection in High-Density Wireless Sensor Networks

Relevance. Increasing the number of sensor devices per unit area consequently reduces the physical distance between the devices in the sensor network. Such networks are usually deployed over a large area and the sensor device that wants to transmit a data packet is located far away from the base station. In such a case, the source device is challenged to choose a transmission path that consumes the least amount of energy resources and satisfies the delivery time requirements. The objective of this study is to develop and validate the effectiveness of an empirical algorithm for selecting a transmission path that reduces the energy consumption of high-density wireless sensor networks. Methods of system analysis, analytical modeling, geometry and probability theories are used. Solution. It is assumed that the sensor network is deployed in a limited area and is a set of devices that are connected to each other informationally and energetically. When building data transmission routes, any sensor devices can be used as repeaters. At the same time, the increase in the number of repeaters leads to an increase in the time of data delivery. Novelty. It is assumed that the sensor network is deployed in a limited area and is a set of devices that are connected to each other informationally and energetically. Any sensor devices may be used as repeaters when constructing data transmission routes.Significance (theoretical). Dependences of power consumption level on various system parameters affecting the processes of functioning of high-density wireless sensor networks have been obtained. Significance (practical). The proposed empirical algorithm for selecting a rational data transmission route in a wireless sensor network allows us to determine, among all alternatives, the route to the coordinator that requires the least power. The effectiveness of the proposed empirical power-saving algorithm is confirmed by simulation modeling.

Optimizing delivery routes for sustainable food delivery for multiple food items per order

The diversity of consumer demand for take-out food has led to the characteristic structure of one order with multiple items, where the different food items in a single order are provided by two or more merchants. In the context of multi-item delivery for take-out orders with time windows, this study investigates vehicle routing for order delivery. This research aims to improve the service level of merchants and the efficiency of delivery vehicles. Food vendors receive orders from consumers through online platforms, then package the food items according to the orders. This method is a preliminary exploration of the issue of fulfilment of takeout orders on online platforms, and can provide preliminary theoretical support for decision-making on the delivery process of takeout orders on online platforms. In the context of online catering sales platforms and offline food sales merchants, this paper studies the delivery problem of takeaway orders with a time window and the characteristics of one order and multiple items, and constructs a method that takes the order delivery time requirements into account and minimizes the total order fulfilment cost. Taking into account the time window constraints of both physical restaurants and consumers, genetic algorithms are utilized to solve the order delivery problem. Finally, through case studies and experiments, the effectiveness and feasibility of the mathematical model are validated. Practical recommendations and insights are provided from the perspective of management and route planning.

Two-stage stochastic programming with robust constraints for the logistics network post-disruption response strategy optimization

Logistics networks (LNs) are essential for the transportation and distribution of goods or services from suppliers to consumers. However, LNs with complex structures are more vulnerable to disruptions due to natural disasters and accidents. To address the LN post-disruption response strategy optimization problem, this study proposes a novel two-stage stochastic programming model with robust delivery time constraints. The proposed model jointly optimizes the new-line-opening and rerouting decisions in the face of uncertain transport demands and transportation times. To enhance the robustness of the response strategy obtained, the conditional value at risk (CVaR) criterion is utilized to reduce the operational risk, and robust constraints based on the scenario-based uncertainty sets are proposed to guarantee the delivery time requirement. An equivalent tractable mixed-integer linear programming reformulation is further derived by linearizing the CVaR objective function and dualizing the infinite number of robust constraints into finite ones. A case study based on the practical operations of the JD LN is conducted to validate the practical significance of the proposed model. A comparison with the rerouting strategy and two benchmark models demonstrates the superiority of the proposed model in terms of operational cost, delivery time, and loading rate.

A matheuristic for the generalized order acceptance and scheduling problem

In make-to-order production systems, manufacturer can have limited capacity and due to the order delivery time requirements, it may not be possible to accept all orders. This leads to the order acceptance and scheduling problem with release times and sequence dependent setup times that determines which orders to accept and how to schedule them simultaneously to maximize the revenue (GOAS). The aim of this study is to develop an effective and efficient solution methodology for the GOAS problem. To achieve this aim, we develop a mixed integer linear programming model, a constraint programming model, and a matheuristic algorithm that consists of a time-bucket based mixed integer linear programming model, a variable neighborhood search algorithm and a tabu search algorithm. Computational results show that the proposed matheuristic outperforms both the proposed exact models and previous state-of-the-art algorithms developed for the GOAS problem. The boundary of optimally solved instance size is pushed further and near optimal solutions are obtained in reasonable time for instances falling beyond this boundary.

Generalized order acceptance and scheduling problem with batch delivery: Models and metaheuristics

This paper addresses an extended version of the generalized order acceptance and scheduling problem by including the logistics aspects into the production scheduling decisions. While order acceptance and scheduling feature of the problem includes the joint decision of which orders to accept and how to schedule them due to the limited capacity in production environment and due to the order delivery time requirements for the customers, logistics aspect of the problem entails the decision of how to batch the accepted orders for the delivery in conjunction with the production scheduling. The objective is to maximize the net revenue in line with the literature of order acceptance and scheduling problem. We first present a mixed integer linear programming and a constraint programming model for this problem. To tackle large size problem instances in which these models fail, we propose an iterated local search algorithm using a new local search scheme. To evaluate the performance of the proposed local search scheme, a variant of this algorithm is developed which replaces the relevant scheme with tabu search. Computational results show that the proposed models achieve small optimality gaps for the small size problems, but their performances deteriorate significantly as the problem size enlarges. For the large size problem instances, the iterated local search algorithm using the proposed local search scheme achieves smaller optimality gaps compared to the one with the tabu search algorithm.

Use of blockchain technology as supply chain management system involving air transport

This article explores Blockchain Technology, and how it can be used in the context of information exchange between stakeholders in international supply chains and networks involving air transport. The article reviews the global experience with this technology of iconic companies (Maersk, Lufthansa, Walmart, Unilever, Nestle, Samsung, British Airways) in logistics and supply chain management. It highlights the features of international chains using air transport, which predominantly consist of two categories of goods: goods with high added value (electronic devices and their components, fashion industry products, jewelry) and goods with strict delivery time requirements (pharmaceuticals, live animals, perishable products, e-commerce products and mail). The study shows that perishable goods have great potential for increasing airline cargo turnover. However, at present, there is no single universal tool for managing their supply chains since the tools used (ERP, SRM, TMS, WMS) do not provide complete transparency of information exchange between all stakeholders. The most problematic stage in the delivery to control steps in the delivery of perishable goods by air occur on the ground, while goods are being handled at the airport of departure and the airport of destination. Difficulties arise while checking the correctness of paperwork, labeling and information authenticity about the product origin. The article suggests using block chain blockchain technology in combination with IoT and smart-contract technologies for SCM of perishable products using air transport. The use of this technology allows to reduce the time of document verification procedures. Customs clearance and phytosanitary control could be vastly improved. Overall tracking and monitoring of a product from the moment of its production to the destination simplifies the identification of any counterfeits, improves the quality of food safety control. A greater level of control becomes possible in logistics operations, to determine liability in possible delivery conditions’ violations cases. Overall optimization of the logistic processes, automatization of the execution of verified financial transactions can be achieved. The use of these technologies in combination with innovative technologies for food quality control will significantly reduce logistics costs in the supply chains of perishable products.

Discrete-Time Analysis of Levelled Order Release and Staffing in Order Picking Systems

Order picking systems are confronted with a volatile demand and short delivery time requirements. Manufacturing companies face the increasing variability requirements with Heijunka-levelling, one method of the Toyota Production System. The objectives of this publication are to develop a levelling concept for order picking systems, to analyse its performance based on a discrete-time analytical model and to develop a staffing algorithm determining the required workforce level in an order picking system with levelled order release. The levelling concept for order picking systems results from the existing models of Heijunka-levelling in the literature, which are adopted and expanded regarding the specific requirements of order picking systems. The order picking system with levelled order release is depicted as a discrete-time Markov chain. To analyse its performance, we derive several performance measures, such as service level, backlog duration and system utilisation, from the steady-state distribution of the Markov chain. The s taffing a lgorithm i s a binary search algorithm based on the Markov chain. The models developed in this publication enable a quantitative evaluation of the impact of several system parameters, such as variability of customer demand, workforce level and traffic intensity, on the performance measures of the order picking system. Furthermore, the staffing algorithm determines the workforce level which is required to guarantee a certain system performance, such as a service level of 99%, in an order picking system with levelled order release. By comparing levelled order release to FCFS-based order release strategies in a numerical example, we show the benefits of levelled order release.

Optimized Train Path Selection Method for Daily Freight Train Scheduling

Train timetables are usually established far in advance of operations and are based on forecasted demands. However, due to changes in actual freight traffic, railways need to determine the actual operation of trains arising in daily operations through train path selection, i.e., selecting a portion of the timetable for these trains to execute. To improve current freight train scheduling in daily operations, this paper suggests taking into account the car flow transfer between consecutive trains and shipment delivery time requirements. A train path selection optimization model is developed to minimize the total travel time of freight trains while seeking minimum penalties for shipment delivery delays. A tabu search algorithm is designed to solve this problem. The effectiveness of the proposed model and algorithm is demonstrated by numerical experiments on instances built on real data from the Menghua railway, a rail freight corridor. The results show that, compared to current practice, this optimization method can achieve a reduction in total train travel time and ensure the punctual delivery of shipments.

ROLE OF VENDOR RESPONSIVENESS ON PROCUREMENT PERFORMANCE AMONG GOVERNMENT MINISTRIES IN KENYA

Purpose: The main objective of the study was to examine the role of vendor responsiveness on procurement performance among government ministries in Kenya.Methodology: Descriptive research design was adopted. The study preferred this method because it allowed an in-depth study of the subject. The study used a sample size of 156 procurement staff. Census will be used in this study. Questionnaires were used to collect data. The questionnaires were tested for validity and reliability using 10% of the total sample respondents. Data was analysed through descriptive statistical methods such as means, standard deviation, frequencies and percentage. Inferential analyses were used in relation to correlation analysis and regression analysis to test the relationship between the four explanatory variables and the explained variable. Multiple regression models were used to show the relationship between the predicted variable and the predictor variables.Results: The findings of the study indicated that delivery time responsiveness, technical requirement responsiveness, financial requirement responsiveness and specifications requirement responsiveness have a positive relationship with procurement performance among government ministries.Conclusion: Based on the study findings, the study concludes that performance of government ministries can be improved by delivery time requirement responsiveness, technical requirement responsiveness, financial requirement responsiveness and specifications requirement responsiveness.Policy recommendation: The study recommended that institutions should embrace vendor responsiveness measures so as to improve procurement performance and further researches should to be carried out in other institutions to find out if the same results can be obtained.

ROLE OF VENDOR RESPONSIVENESS ON PROCUREMENT PERFORMANCE AMONG GOVERNMENT MINISTRIES IN KENYA

Purpose: The main objective of the study was to examine the role of vendor responsiveness on procurement performance among government ministries in Kenya.Methodology: Descriptive research design was adopted. The study preferred this method because it allowed an in-depth study of the subject. The study used a sample size of 156 procurement staff. Census will be used in this study. Questionnaires were used to collect data. The questionnaires were tested for validity and reliability using 10% of the total sample respondents. Data was analysed through descriptive statistical methods such as means, standard deviation, frequencies and percentage. Inferential analyses were used in relation to correlation analysis and regression analysis to test the relationship between the four explanatory variables and the explained variable. Multiple regression models were used to show the relationship between the predicted variable and the predictor variables.Results: The findings of the study indicated that delivery time responsiveness, technical requirement responsiveness, financial requirement responsiveness and specifications requirement responsiveness have a positive relationship with procurement performance among government ministries.Conclusion: Based on the study findings, the study concludes that performance of government ministries can be improved by delivery time requirement responsiveness, technical requirement responsiveness, financial requirement responsiveness and specifications requirement responsiveness.Policy recommendation: The study recommended that institutions should embrace vendor responsiveness measures so as to improve procurement performance and further researches should to be carried out in other institutions to find out if the same results can be obtained.

The value of specific cargo information for substitutable modes of inland transport

Communication about containers onboard a cargo carrier approaching a harbor with a hinterland operator who is to receive the containers usually reveals the total amount of goods (aggregate number of containers) to be transported inland upon unloading at the arrival dock. This communication is useful for the hinterland operator to plan and deploy its transport capacities. However, further transport of containers on the hinterland involve various transport modes at differing costs. For example, the delivery time requirement of a container dictates the most appropriate mode of inland transport, be it truck, rail, or barge, in decreasing order of speed, flexibility and cost, to move the container to the next destination. In general there may be several types of delivery time requirements and containers of each type is most economically moved inland in a corresponding transport mode. Trucking is usually used for containers that need urgent delivery and train or barge for not so urgent types. In order to efficiently plan the transport capacities for after-arrival conveyance of containers having multi-type delivery time requirements, not only should the aggregate number of containers, but also the number of containers of each type, be made available to the hinterland operator. We consider several information scenarios and in each scenario we solve a single-period capacity planning serving multi-type demands with product substitution. We then compare expected transport costs between information scenarios to evaluate the benefit of specific cargo information in improving the next-step transporting after containers are unloaded at the port of entry.

4PL routing optimization under emergency conditions

Routing optimization is one of important problems in fourth party logistics (4PL) management. Under emergency conditions, effectively describing uncertain parameters for routing optimization entails major challenges because of a lack of historical data. Hence, this paper studies a fourth party logistics routing optimization problem (4PLROP) with uncertain delivery time under emergency conditions. A novel 4PLROP uncertain programming model (UPM) under emergency conditions is proposed by describing the uncertain delivery time as an uncertain variable based on the uncertainty theory (UT) first. Then, to justify the advantage of UPM for addressing this problem with little historical data, UPM is compared with the stochastic programming model (SPM) in which the uncertain delivery time is described as a stochastic variable based on probability theory. The comparison results show that the UPM solution can satisfy the belief degree constraint, which is used to describe the customer delivery time requirement, whereas the SPM solution cannot. Finally, numerical examples are used to verify the effectiveness of the proposed method. The results also suggest the proposed model’s advantages.

QoS-aware resource management for LTE-Advanced relay-enhanced network

Relaying is one of the major innovative concepts proposed in the recent years for cellular radio communication systems. It is a perfect solution for dealing with the issue of high variability of performance in cellular networks. By coordinated deployment at cell-edge or in shadowed areas, relay nodes can extend network coverage and increase the low end-user performance. Considering the advantages, relaying is recently being included in the standards of the fourth generation systems such as the LTE-Advanced and the WiMAX. However, one major problem of relaying is still to be resolved. Specifically, there are no concrete concepts for quality-of-service provisioning for relayed transmissions. This paper investigates the case of packet delivery times over multi-hop links in relay-enhanced networks. The discussion is specifically based on relaying implementation in the LTE-Advanced system. The quality-of-service satisfaction and its fairness for the base station and relay-node-connected users are analyzed in the framework of the utility theory. For the purpose of this analysis, utility functions are proposed for real-time traffic with minimum data rate and/or maximum packet delivery time requirements. Furthermore, several optimization concepts are proposed for managing multi-hop transmissions in a quality-of-service aware manner. The included analysis based on the LTE-Advanced system level simulations shows that the proposed optimizations have the potential to improve the overall quality-of-service satisfaction in a relay-enhanced system.

Optimizing shipping-fee schedules to maximize e-tailer profits

Shipping-fee charges by online retailers have been known to impact customers' order incidence and cart size. While the importance of managing shipping fees is well documented, few studies have provided normative guidelines for e-tailers to determine optimal shipping-fee schedules. This paper provides two nonlinear mixed-integer programming models to optimize e-tailers' shipping-fee charges for single and multiple product transactions. Given e-tailers' cost information and heterogeneity across consumers' reservation prices and delivery time requirements, our models aim to concurrently determine the optimal shipping-fee schedules and product selling prices. To solve the sophisticated models in real-time, we develop search techniques based on the concept of genetic algorithms. Numerical studies indicate that the proposed methods offer attractive product prices and low shipping charges. The proposed models not only meet the online requirement of instant response time, but also draw more customers and enhance e-tailer profitability.

Change Order Audit in Machinery Enterprise Base on the Delivery Schedule and Loss Cost Estimate

When order change happens, enterprises hope to be able to estimate the earliest/latest and loss cost. This can help make the produce plan and meet the delivery time requirements of customers. In this paper, model to estimate the loss cost and delivery time caused by order change is built. Also, method to audit order change by level constraint is proposed.

Inducing high service capacities in outsourcing via penalty and competition

In this article, we consider a model of multiple make-to-order suppliers, which compete based on their promised sojourn times. A fixed penalty is imposed on the suppliers for failing the promised delivery time requirement at an agreed service level. The demand is allocated to the suppliers according to the promised sojourn times, using either supplier-selection (SS) approach or supplier-allocation (SA) approach as proposed in Benjaafar et al. (2007, Outsourcing via service competition, Management Science, 53 (2), 241–259). Their framework and results are then applied to obtain the competition outcome. It was found that the buyer can orchestrate the competition to induce the suppliers to offer lower promised sojourn times and select higher service capacities through restricting the suppliers to choose promised sojourn times above a certain level. The SS approach is also found to induce a better service quality than the SA approach. The role of the penalty level is then addressed. It was found that a higher penalty level induces a higher service capacity and is always beneficial to the buyer.

Product Scheduling for Thermal Energy Reduction in Papermaking Industries

AbstractPapermaking is considered as an energy-intensive industry partly due to the fact that the machinery and procedures have been designed at the time when energy was both cheap and plentiful. A typical paper machine manufactures a variety of different products (grades) which impose variable per-unit raw material and energy costs to the mill. It is known that during a grade change operation the products are not market-worthy. Therefore, two different production regimes, i.e. steady state and grade transition can be recognised in papermaking practice. Among the costs associated with paper manufacture, the energy cost is ‘more variable’ due to (usually) day-to-day variations of the energy prices. Moreover, the production of a grade is often constrained by customer delivery time requirements. Given the above constraints and production modes, the product scheduling technique proposed in this paper aims at optimising the sequence of orders in a single machine so that the cost of production (mainly determined by the energy) is minimised. Simulation results obtained from a commercial board machine in the UK confirm the effectiveness of the proposed method.

Design of Dry Pipe Sprinkler Systems to Meet the Water Delivery Time Restriction in Industrial Freezers

Dry-pipe sprinkler systems are commonly used when the ambient temperature of a protected space is below freezing temperature of water. Because the degree of fire spread prior to sprinkler actuation is greater than that of the wet system in comparable circumstances, a greater coverage area is often required in a drysystem than that of a wet system. In addition, the dry system also requires the water delivery time to the most remote sprinkler be within a certain time limit. Dry-pipe ceiling-sprinkler restriction imposed by NFPA 13 for the protection of Class 2 materials in rack-storage higher than 7.6-m under 12-m ceiling is a maximum 30-seconds water delivery time with a 4-heads-open assumption. An in-house computer program developed to estimate water delay times in dry-pipe systems has been extensively used at FM Global for the last 15 years to address the water delivery time requirement mentioned above for industrial freezers. This paper describes how the program was developed and how the 30-seconds water-delivery time requirement could be met by choosing proper operating conditions through numerous real design cases. The examples showed that by adjusting many operating control parameters, most of the system could meet the 30-seconds water delivery time restriction without making substantial alteration in system configurations. The case study also shows that the air trip time linearly increases with the system volumes as anticipated. The water transit time also increases with the system volume in general, however, the dependence was more complex, which indicates that the system configuration plays an important role in the transit time in dry-pipe systems. Overall, the case study shows that the program had enabled the system design to be much more flexible and cost effective.

SU‐FF‐T‐07: A Comparative Analysis Between Conventional MLC Based and Solid Compensator Based IMRT Treatment Techniques. A Clinical Review After 5 Years

Purpose: The goals of this study were to evaluate the clinical differences of solid and MLC based IMRT treatments. Dosimetric comparison of the dose outside the target volume at various depths was carried out. The investigation was extended to compare delivery time and monitor unit requirements for IMRT techniques. Methods and Material: The ADAC Pinnacle inverse planning system was used to generate MLC based IMRT plans. Using .decimal software, ADAC was also used to generate compensator based IMRT plans. Plans were generated for the following target volumes, prostate, adrenal gland, brain, and head and neck. The delivery time, number of monitor units and the fluence intensity maps were compared. Dose points outside the target volume were compared to determine out of target doses. Delivery of treatment plans was performed on a Rando phantom and mosfet dosimeters, gaf chromic film and TLDs were used to compare measured doses of MLC and solid IMRT treatments. Results: For the more complex plans the solid compensators resulted in 26.7% fewer monitor units and delivery time was reduce in half when compared with MLC plans. However for relatively simple IMRT plans such as prostate boosts or adrenal gland plans were the target has a relatively simple cylindrical shape the MLC plans resulted in an average of 41.6% fewer MUs and required about 16% less time to deliver than the solid compensator plans. Mosfet skin dose analysis showed that the solid compensators resulted in an average of 17.5% less dose. Conclusions: Based on the measured results it is evident that solid compensators are a viable IMRT treatment option when considering complex target arrangements that require many beams segments. For relatively simple plans which result in fewer and larger beam segments compensator based plans showed no advantage over MLC plans in regards to MUs and treatment time.

Influences of external digital environment, markets and terminal price elasticity on personal satellite systems

AbstractAlthough there is no doubt about the feasibility of personal communications via small satellites in low earth orbit, there is considerable uncertainty about the size of the market, whether the specific applications will be business or personal in context, about the market relationship between voice services and data services, and the implications for system design of any information that might be developed on these questions.This paper will develop the concept that the key to understanding low orbit small satellite communications systems is the message delivery time requirement of markets and that the data services market has a widely varying range of acceptable data delivery times. We estimate the distribution of data delivery time versus population of users on a global basis.A second concept to be developed in this paper is that low orbit satellites are in some respects matched to global data delivery applications because of the daylight time zones and natural delays they impose.Using the estimated market size versus message delivery time, we show that there is a significant design implication for the space segment in terms of the number of satellites, the orbit period, and the use of crosslinks. It will be further shown that the difference in complexity of data and voice services with respect to cost argues for the rapid emergence and success of data services.Finally, we will show that a preferred terminal architecture may be an accessory or applique for a personal computer, rather than a small dedicated satellite terminal, based on the extant population of personal computers. A review of the planned terminal architectures of emerging systems reveals that using a personal computer as the basis for a terminal has not yet received wide interest. In particular, the new laptop smaller computers may be the natural catalyst for personal satellite data services in facilitating the terminal.