Delivery Quantity Research Articles

Modelling construction material logistics system with stochastic Petri nets

PurposeThe purpose of this paper is to examine the potential of applying Petri nets to improve construction material logistics analysis and modelling.Design/methodology/approachThe characteristics of construction logistics are unveiled by analysing the existing practices of logistics management. In views of the dynamic nature of construction logistics problem, a stochastic Petri nets (SPNs) approach is proposed to tackle the time‐evolution property. Using a simulation package called PetriTool™ a simulation model is developed. Finally, a case example is applied to illustrate the way in which SPNs is used for analysing and modelling construction material logistics problems.FindingsThe results indicate that the impacts triggered by variations in delivery lead‐time and changes in delivery quantities can be approximated thereby facilitating decision makers to devise a more reliable and optimal materials management plan for construction projects.Research limitations/implicationsThe complex routing patterns in demand analysis and materials procurement methods that results in the enlarged supply chains have not been considered in this paper.Practical implicationsThe lack of a simple but powerful formalism to analyse and model the decision process under a dynamic environment hinders the implementation of efficient logistics systems in the construction industry. The SPNs model presented in this paper can support planners and managers in making construction logistics management decisions under dynamic environment.Originality/valueThis paper demonstrates that the time‐based SPNs can offer more enriched solutions especially when modelling the time‐evolution behaviours of construction logistics.

Heuristic approaches for determining minimum cost delivery quantities in supply chains

In this paper, we consider heuristic approaches for the determination of delivery quantities in a Supply Chain (SC). The problem under consideration is important for the design of delivery quantity negotiations between manufacturers and suppliers. We describe a Mixed Integer Programming (MIP) formulation for the optimisation problem to be solved. We explain how we can incorporate and use the suggested decision model into a decision-support system for Supply Chain Management (SCM). Because of the computational intractable large-sized mixed integer programs, we describe an efficient Genetic Algorithm (GA) in order to get near-to-optimal solutions of the mixed integer programs. We compare the GA with a Random Search Heuristic and a Branch and Bound (B&B) algorithm to solve the mixed integer programs. The different solution procedures are assessed with respect to solution quality and computational time based on stochastically generated test instances. The GA produces high-quality solutions with an acceptable computational effort. [Received 20 December 2006; Revised 01 June 2007; Second Revision Received 06 October 2007; Accepted 06 December 2007]

Supplier selection in an agile manufacturing environment using Data Envelopment Analysis and Analytical Network Process

Supplier selection is one of the most important activities of organisations, where the short- and long term success of a buyer's organisation depends upon proper selection of its suppliers. The current competitive environment has placed increasing competitive pressures on suppliers to match the needs of buyer(s) in terms of quantity, quality, product mix, cost, time and place of delivery, to name a few performance measures. The focus on competitive supply chains and extended enterprises requires the adoption of agile manufacturing practices requiring their suppliers to have agile attributes. This study designs and implements a procedure for judging the suitability of suppliers for an organisation competing on agile manufacturing characteristics. Quantitative and qualitative factors are used to appraise and select appropriate suppliers to fit within an organisation's agility practices. In seeking to achieve this task, the synergistic integration of two techniques, the Analytical Network Process (ANP) and Data Envelopment Analysis (DEA) is applied in a multi-phased supplier selection approach. Initially, ANP is executed to appraise suppliers on their qualitative benefits, generating quantitative data from these qualitative dimensions. Secondly, DEA is used to synthesise the data to arrive at a ranking of the suppliers. The technique is validated in a small company case study.

Managing quality improvement, setup cost and lead time reductions in a just-in-time integrated inventory model

This article investigates a just-in-time integrated inventory model with quality improvement, setup cost and lead time reduction. The objective is to simultaneously optimise the order quantity, setup cost, process quality level, number of deliveries and lead time. A solution procedure is suggested for solving the proposed model and a numerical example is considered to illustrate the impact of setup cost reduction with capital investment. The current model predicts a lower total cost, order quantity and number of deliveries compared with Yang, J-S. and Pan, J.C-H. (2004) 'Just-in-time purchasing: an integrated inventory model involving deterministic variable lead time and quality improvement investment', Int. J. Production Research, Vol. 42, pp.853-863. An integrated inventory model is helpful in breaking down the traditional barriers as it results in lower total relevant cost compared to the independent inventory policies of both purchaser and vendor. These results can be used to promote cooperation and to minimise the total system cost of integrated enterprises.

A zero-inventory production and distribution problem with a fixed customer sequence

In this paper, we study the zero-inventory production and distribution problem with a single transporter and a fixed sequence of customers. The production facility has a limited production rate, and the delivery truck has non-negligible traveling times between locations. The order in which customers may receive deliveries is fixed. Each customer requests a delivery quantity and a time window for receiving the delivery. The lifespan of the product starts as soon as the production for a customer’s order is finished, which makes the product expire in a constant time. Since the production facility and the shipping truck are limited resources, not all the customers may receive the delivery within their specified time windows and/or within product lifespan. The problem is then to choose a subset of customers from the given sequence to receive the deliveries to maximize the total demand satisfied, without violating the product lifespan, the production/distribution capacity, and the delivery time window constraints. We analyze several fundamental properties of the problem and show that these properties can lead to a fast branch and bound search procedure for practical problems. A heuristic lower bound on the optimal solution is developed to accelerate the search. Empirical studies on the computational effort required by the proposed search procedure comparing to that required by CPLEX on randomly generated test cases are reported.

Brief Intervention in Type 1 diabetes – Education for Self-efficacy (BITES): Protocol for a randomised control trial to assess biophysical and psychological effectiveness

BackgroundSelf management is the cornerstone of effective preventive care in diabetes. Educational interventions that provide self-management skills for people with diabetes have been shown to reduce blood glucose concentrations. This in turn has the potential to reduce rates of complications. However, evidence to support type, quantity, setting and mode of delivery of self-management education is sparse.Objectives: To study the biophysical and psychological effectiveness of a brief psycho-educational intervention for type 1 diabetes in adults.Methods/DesignDesign: Randomised controlled clinical trial.Setting: Multidisciplinary specialist diabetes centre.Hypothesis: Our hypothesis was that the brief (2.5-day) intervention would be biophysically and psychologically effective for people with type 1 diabetes.Intervention: A brief psycho-educational intervention for type 1 diabetes developed by a multi-professional team comprising of a consultant diabetologist, a diabetes specialist nurse, a specialist diabetes dietician and a clinical health psychologist and delivered in 20 hours over 2.5 days.Primary outcomes: HbA1c and severe hypoglycaemia.Secondary outcomes: Blood pressure, weight, height, lipid profile and composite psychometric scales.Participants: We shall consent and recruit 120 subjects with postal invitations sent to eligible participants. Volunteers are to be seen at randomisation clinics where independent researcher verify eligibility and obtain consent. We shall randomise 60 to BITES and 60 to standard care.Eligibility Criteria: Type 1 diabetes for longer than 12 months, multiple injection therapy for at least two months, minimum age of 18 and ability to read and write.Randomisation: An independent evaluator to block randomise (block-size = 6), to intervention or control groups using sealed envelopes in strict ascendant order. Control group will receive standard care.Assessment: Participants in both groups would attend unblinded assessments at baseline, 3, 6 and 12 months, in addition to their usual care. After the intervention, usual care would be provided.Ethics approval: York Research Ethics Committee (Ref: 01/08/016) approved the study protocol.DiscussionWe hope the trial will demonstrate feasibility of a pragmatic randomised trial of BITES and help quantify therapeutic effect. A follow up multi-centre trial powered to detect this effect could provide further evidence.Trial registrationCurrent Controlled Trials ISRCTN75807800

A NEW APPROACH OF FLEXIBILITY PLANNING A REALITY OR A SEARCH OF THE HOLY GRAIL!

In the new context of “contract-order”, companies are engaged with their customers on a global program of delivery orders. Each order concerns the deliver of quantities (varying between a minimum and a maximum value) of products at precise moments. The exact quantities are known only few days before the delivery. This variability of delivery quantities needs the management in an efficient way of some flexibility levers in order to guarantee the service engagement and minimize the costs. In this paper, a new approach of flexibility planning will be presented. This approach tends to satisfy these goals and takes into account internal and external constraints of these companies. The most important internal constraint is the evidence presence of a bottleneck resource. An external constraint must be obviously satisfied which is the imposed regulations.

Development of a New Horizontal Rotary GDP Coater Enabling Increased Production

Providing glow discharge polymer (GDP) coatings is a key step in Inertial Confinement Fusion (ICF) target production. Typical target delivery quantities may require several GDP coating runs consisting of up to 80 mandrels per batch. This work undertakes research and development to create a new configuration for the GDP coating apparatus that will enable batch sizes into the hundreds or thousands. This will reduce costs associated with target production and make delivery of ICF targets more efficient. In addition, there is a synergy between this work and Inertial Fusion s’Energy (IFE’s) need for half a million targets per day for energy production, as well as future commercial applications. Recently we have demonstrated the capability to meet the NIF CH surface standard, confirmed via statistical sampling, in a 400 capsule batch coated with 10 μm of GDP, a key benchmark for successful coatings.

Inventory rationing and sharing in pre-sell distribution with mobile communication technologies

In pre-sell distribution, the uncertain customer demands are revealed by the company's sales representatives who visit the customers and arrange delivery quantities on the spot, prior to physical execution of deliveries. Given a periodic base-stock of a distributed product, we consider allocation of the product to the customers in two different settings: with and without utilization of mobile communication technologies. There are two performance measures considered: the customer-average fill rate, and the sales profit under service level constraints. The mobile setting is shown to enable a generally better system-wide performance, featuring the capability of inventory pooling. To observe the magnitude of this advantage we determine the optimal allocation policies by means of stochastic dynamic programming. Computational examples for selected configurations and demand distributions are presented.

Cyclic production for cyclic deliveries

Nowadays, companies frequently work with their customers in contract-order with fixed and cyclic delivery dates. The exact delivery quantities are usually known only a few days before the delivery. This kind of contract is found very frequently, especially in the big distribution and the automotive sectors. The utilisation of classical methods of production management does not seem efficient enough to face this kind of demand. This paper presents a methodological framework for the implementation of cyclic production modes. We consider a factory which produces n items in a facility and which is confronted with a cyclic demand: each item is ordered relative to a cyclic delivery schedule with a mean quantity for each delivery. We propose, on a medium-term level, a set of methods (optimal and heuristic) to build cyclic production schedules. Then we compare these methods and specify how and when they can be used. Finally, a more general use of these methods and the possible extensions are discussed.

Master Production Scheduling and a comparison of Material Requirements Planning and cover-time planning

For a company's long-term profitability, the most important processes are the way it starts parts of the manufacturing process before the customer order arrives and the way it determines and promises delivery quantities and times for customer orders. In practical computer applications Material Requirement Planning (MRP) and/or Reorder point systems are the base techniques mostly used. This paper presents Cover-Time Planning (CTP), a variant of a reorder point system, which is developed with a forward-looking forecasted demand rate and the decision variable is ‘time’, instead of ‘quantity’ for an ordinary reorder-point system. MRP and CTP are introduced and compared through a numerical example. MRP and CTP must treat a practical ‘make-to-order’; therefore, this paper discusses available-to-promise, planning bills and other help systems for practical applications of Master Production Scheduling. The paper presents how and why, in practice, a Master Production Scheduling system with an available-to-promise function should be used and how this system should be designed. It is also argued that a fully Enterprise Resource Planning (ERP) system cannot only be created by MRP, but also by CTP.

The Vehicle Routing Problem with Demand Range

We propose and formulate the vehicle routing problem with demand range (VRPDR), a new variation on the traditional vehicle routing problem. In the VRPDR, the delivery quantity for each customer i is allowed to vary from its original size di by an amount αdi where 0 ≤ α< 1. In adding this limited flexibility to the problem, there is potential to generate significant savings in the total distance traveled. We address issues such as bounding the impact of a given α on total distance and provide empirical results to illustrate "typical" behavior.

Impact of phosphorus control measures on in-river phosphorus retention associated with point source pollution

Abstract. In-river phosphorus retention alters the quantity and timings of phosphorus delivery to downstream aquatic systems. Many intensive studies of in-river phosphorus retention have been carried out but generally on a short time scale (2-4 years). In this paper, monthly water quality data, collected by the Environment Agency of England and Wales over 12 years (1990-2001), were used to model daily phosphorus fluxes and monthly in-river phosphorus retention in the lowland calcareous River Wensum, Norfolk, UK. The calibrated model explained 79% and 89% of the observed variance before and after phosphorus control, respectively. A split test revealed that predicted TP loads were in good agreement with observed TP loads (r2=0.85), although TP loads were underestimated under high flow conditions. During relatively dry years, there was no net export of phosphorus from the catchment. High retention of phosphorus occurred, particularly during the summer months, which was not compensated for, by subsequent higher flow events. This was despite a relatively modest critical discharge (Q) above which net remobilisation occur. Phosphorus removal from the effluent at two major STWs (Sewage Treatment Works) reduced phosphorus retention but not the remobilisation. This may indicate that the presence of impoundments and weirs, or overbank flows may have more control on the phosphorus dynamics under high flow conditions. Further phosphorus remedial strategies will be necessary to prevent downstream risks of eutrophication occurring independently of the unpredictable variability in weather conditions. More research is also needed to quantify the impact of the weir and overbank flows on phosphorus dynamics.

Pulsatile Insulin Secretion Dictates Systemic Insulin Delivery by Regulating Hepatic Insulin Extraction In Humans

In health, insulin is secreted in discrete pulses into the portal vein, and the regulation of the rate of insulin secretion is accomplished by modulation of insulin pulse mass. Several lines of evidence suggest that the pattern of insulin delivery by the pancreas determines hepatic insulin clearance. In previous large animal studies, the amplitude of insulin pulses was related to the extent of insulin clearance. In humans (and in large animals), the amplitude of insulin oscillations is approximately 100-fold higher in the portal vein than in the systemic circulation, despite only a fivefold dilution, implying preferential hepatic extraction of insulin pulses. In the present study, by direct hepatic vein sampling in healthy humans, we sought to establish the extent of first-pass hepatic insulin extraction and to determine whether the pattern of insulin secretion (insulin pulse mass and amplitude) dictates the hepatic insulin clearance and thereby delivery of insulin to extrahepatic insulin-responsive tissues. Five nondiabetic subjects (two men and three women, mean age 32 years [range 25-39], BMI 24.9 kg/m(2) [21.2-27.1]) participated. Insulin and C-peptide delivery from the splanchnic bed was measured in basal overnight-fasted state and during a glucose infusion of 2 mg . kg(-1) . min(-1) by simultaneous sampling from the hepatic vein and an arterialized vein along with direct estimation of splanchnic blood flow. Fractional insulin extraction was calculated from the difference between the C-peptide and insulin delivery rates from the liver. The time patterns of insulin concentrations and hepatic insulin clearance were analyzed by deconvolution and Cluster analysis, respectively. Cross-correlation analysis was used to relate C-peptide secretion and insulin clearance. Glucose infusion increased peripheral glucose concentrations from 5.4 +/- 0.1 to 6.4 +/- 0.4 mmol/l (P < 0.05). Likewise, insulin and C-peptide concentrations increased during glucose infusion (P < 0.05). Hepatic insulin clearance increased with glucose infusion (1.06 +/- 0.18 vs. 2.55 +/- 0.38 pmol . kg(-1) . min(-1); P < 0.01), but fractional hepatic insulin clearance was stable (78.2 +/- 4.4 vs. 84 0. +/- 3.9%, respectively; P = 0.18). Insulin secretory-burst mass rose during glucose infusion (P < 0.05), whereas the interburst interval remained unchanged (4.4 +/- 0.2 vs. 4.5 +/- 0.3 min; P = 0.36). Cluster analysis identified an oscillatory pattern in insulin clearance, with peaks occurring approximately every 5 min. Cross-correlation analysis between prehepatic C-peptide secretion and hepatic insulin clearance demonstrated a significant positive association without detectable (<1 min) time lag. Insulin secretory-burst mass strongly predicted insulin clearance (r = 0.81, P = 0.0043). In conclusion, in humans, approximately 80% of insulin is extracted during the first liver passage. The liver rapidly responds to fluctuations in insulin secretion, preferentially extracting insulin delivered in pulses. The mass (and therefore amplitude) of insulin pulses traversing the liver is the predominant determinant of hepatic insulin clearance. Therefore, through this means, the pulse mass of insulin release dictates both hepatic (directly) as well as extra-hepatic (indirectly) insulin delivery. These findings emphasize the dual role of the liver and pancreas and their relationship mediated through magnitude of insulin pulse mass in regulating the quantity and pattern of systemic insulin delivery.

Optimization-Based Available-To-Promise with Multi-Stage Resource Availability

Increasingly, customer service, rapid response to customer requirements, and flexibility to handle uncertainties in both demand and supply are becoming strategic differentiators in the marketplace. Organizations that want to achieve these benchmarks require sophisticated approaches to conduct order promising and fulfillment, especially in today’s high-mix low-volume production environment. Motivated by these challenges, the Available-to-Promise (ATP) function has migrated from a set of availability records in a Master Production Schedule (MPS) toward an advanced real-time decision support system to enhance decision responsiveness and quality in Assembly To Order (ATO) or Configuration To Order (CTO) environments. Advanced ATP models and systems must directly link customer orders with various forms of available resources, including both material and production capacity. In this paper, we describe a set of enhancements carried out to adapt previously published mixed-integer-programming (MIP) models to the specific requirements posed by an electronic product supply chain within Toshiba Corporation. This model can provide individual order delivery quantities and due dates, together with production schedules, for a batch of customer orders that arrive within a predefined batching interval. The model considers multi-resource availability including manufacturing orders, production capability and production capacity. In addition, the model also takes into account a variety of realistic order promising issues such as order splitting, model decomposition and resource expediting and de-expediting. We conclude this paper with comparison of our model execution results vs. actual historical performance of systems currently in place.

Coordination of a Supply Chain with One-Manufacturer and Two-Retailers Under Demand Promotion and Disruption Management Decisions

Increasingly, customer service, rapid response to customer requirements, and flexibility to handle uncertainties in both demand and supply are becoming strategic differentiators in the marketplace. Organizations that want to achieve these benchmarks require sophisticated approaches to conduct order promising and fulfillment, especially in today’s high-mix low-volume production environment. Motivated by these challenges, the Available-to-Promise (ATP) function has migrated from a set of availability records in a Master Production Schedule (MPS) toward an advanced real-time decision support system to enhance decision responsiveness and quality in Assembly To Order (ATO) or Configuration To Order (CTO) environments. Advanced ATP models and systems must directly link customer orders with various forms of available resources, including both material and production capacity. In this paper, we describe a set of enhancements carried out to adapt previously published mixed-integer-programming (MIP) models to the specific requirements posed by an electronic product supply chain within Toshiba Corporation. This model can provide individual order delivery quantities and due dates, together with production schedules, for a batch of customer orders that arrive within a predefined batching interval. The model considers multi-resource availability including manufacturing orders, production capability and production capacity. In addition, the model also takes into account a variety of realistic order promising issues such as order splitting, model decomposition and resource expediting and de-expediting. We conclude this paper with comparison of our model execution results vs. actual historical performance of systems currently in place.

Economical delivery strategies of products in a JIT system under a global supply chain

This study supplies an optimal total cost model, including approach I and approach II, to manufacturers with several assemblers in the same area to decide the most economical product delivery strategy in the global just-in-time (JIT) system. In approach II, manufacturers deliver products to downstream assemblers via a JIT system with third party logistics (3PL) support. There is a distinction between approach I and approach II according to whether or not the delivery quantity is limited to economical delivery lot size. A case study analysis is used to illustrate the proposed models, in which the following conclusions can be obtained. Firstly, the JIT product delivery strategy according to economical delivery lot size can be obtained to achieve a cost-effective global supply chain. Second, upstream manufacturers can apply a JIT system under a global supply chain to downstream manufacturers with lower cost through support from 3PL with economical delivery lot size.

Strategic Positioning of Inventory to Match Demand in a Capital Projects Supply Chain

Industrial buyers of capital facilities have experienced and continue to experience pressure to reduce facility design and construction lead time. This pressure arises both internally (due to successes in manufacturing lead time reductions) and externally (due to competitive forces including narrowing product delivery windows). This paper presents a case study detailing one owner’s efforts to reduce the length and variability of delivery time for long-lead construction materials in order to improve overall project lead time. The owner adopted a long-term multiproject perspective, procuring material in advance of specific projects and holding it at a position in the supply chain selected to allow flexibility for customization. Reduction in lead time of 75% from order to delivery of the material resulted for individual projects within the owner’s capital plan. As a result, the material was available at the construction site well in advance of its need for erection. To study if holding material at alternative locations in the supply chain could provide a better match between delivery quantities and the demand for erection, the supply chain was simulated. In this case study, demand information was imprecise, allowing only the quantity of material delivered to be considered rather than matching specific items to specific locations. Nonetheless, the results demonstrate the utility of simulation in the capital projects supply chain and the value of improving demand forecasts.

Channel coordination in an assembly system facing uncertain demand with synchronized processing time and delivery quantity

Supply chains need to be synchronized to increase system efficiency. With increasing globalization, an assembly or a manufacturing firm may receive supplies from all over the world. Synchronization of such a system becomes difficult for two reasons: first, each supplier has certain capacity and can supply materials with a fixed but different order processing time; second, each supplier has a different cost structure and, therefore, production quantities differ due to incentives conflicts, which leads to local optimization of profits by the suppliers. In the existing literature, this problem is generally tackled by focusing either on the synchronization of order processing time or on order quantity determination. However, when system coordination is of the essence, simultaneous consideration of both becomes imperative. A model to synchronize the assembly process is proposed and the optimal order quantities in a two-echelon assembly system with one assembler (facing a stochastic demand) and multiple suppliers with deterministic order processing times is determined. A numerical study conducted shows that risk sharing and proper safety stock placement lead to better system coordination and improve system performance.

Density-habitat relationships of mangrove creek fishes within the southeastern saline Everglades (USA), with reference to managed freshwater releases

The Comprehensive Everglades Restoration Plan aims to make considerable changes to the quantity, quality, and timing of freshwater delivery to the southeastern saline Everglades (SESE), a mangrove ecosystem located between the freshwater Everglades and downstream estuarine embayments. Whereas fishes inhabiting seasonally-inundated areas of the SESE and the shorelines of downstream embayments have been examined, those utilizing the creeks connecting these ecotones have not. To evaluate the functional role of the creek habitat and the possible impact of future hydrologic changes on the fishes inhabiting them, 228 underwater visual surveys were performed at three locations of the SESE over a three-year period. Fish abundance data was related to structural habitat, water level, and salinity over various time periods. The SESE contains taxa from both the freshwater Everglades and downstream embayments, but does not appear to function as a nursery for most fishery taxa. Abiotic variability and fish diversity increased with distance from major freshwater sources. Though there were significant differences in the physical structure of mangrove trees among locations, few meaningful correlations between these parameters and the density of individual fish taxa were found. Small ‘prey-base’ fishes (<10 cm TL) utilize the expansive ephemeral wetlands (i.e., upper mangle) during wet periods, and were concentrated into deeper creeks when these wetlands became dry. Densities of these fishes increase on the upper mangle with increased flooding (hydroperiod), and we observed greater densities of larger species in the creeks when hydroperiods exceeded 240 days. Based on these results, we recommend that water management create water releases which result in a wet period of ca. 240 days, followed by a gradual dry period lasting ca. 90 days.