Delivery Time Windows Research Articles

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.

Real-time split-delivery pickup and delivery time window problems with transfers

In this research we present the design and implementation of heuristics for solving split-delivery pickup and delivery time window problems with transfer (SDPDTWP) of shipments between vehicles for both static and real-time data sets. In the SDPDTWP each shipment is constrained with the earliest possible pickup time from the origin and the latest acceptable delivery time to a destination. Split-deliveries occur when two or more vehicles service the same origin or destination. The proposed heuristics were applied to both static and real-time data sets. The heuristics computed a solution, in a few seconds, for a static problem from the literature, achieving an improvement of 60% in distance in comparison to the published solution. In the real-time SDPDTWP problems, requests for pickup and delivery of a package, breakdown of a truck or insertion of a truck can occur after the vehicle has left the origin and is enroute to service the customers. Thirty data sets, each consisting of one to seven real-time customer or truck events, were used to test the efficiency of the heuristics. The heuristics obtained solutions to real-time data sets in under five seconds of CPU time.

Vehicle routing problem with time-windows for perishable food delivery

This study has extended a vehicle routing problem, with time-windows (VRPTW), by considering the randomness of the perishable food delivery process, and constructing a SVRPTW model, to obtain optimal delivery routes, loads, fleet dispatching and departure times for delivering perishable food from a distribution center. Our objective was to minimize not only the fixed costs for dispatching vehicles, but also the transportation, inventory, energy and penalty costs for violating time-windows. We also discussed time-dependent travel and time-varying temperatures, during the day, modifying the objective functions as well as the constraints in the above mathematical programming models. Algorithms were developed to solve the proposed models; results indicated that inventory and energy costs can significantly influence total delivery costs. It was found that our proposed models yielded better results than the traditional VRPTW models.

Lot-sizing with production and delivery time windows

We study two different lot-sizing problems with time windows that have been proposed recently. For the case of production time windows, in which each client specific order must be produced within a given time interval, we derive tight extended formulations for both the constant capacity and uncapacitated problems with Wagner-Whitin (non-speculative) costs. For the variant with nonspecific orders, known to be equivalent to the problem in which the time windows can be ordered by time, we also show equivalence to the basic lot-sizing problem with upper bounds on the stocks. Here we derive polynomial time dynamic programming algorithms and tight extended formulations for the uncapacitated and constant capacity problems with general costs.For the problem with delivery time windows, we use a similar approach to derive tight extended formulations for both the constant capacity and uncapacitated problems with Wagner-Whitin (non-speculative) costs.

Lot-Sizing with Production and Delivery Time Windows

We study two different lot-sizing problems with time windows that have been proposed recently. For the case of production time windows, in which each client specific order must be produced within a given time interval, we derive tight extended formulations for both the constant capacity and uncapacitated problems with Wagner-Whitin (non-speculative) costs. For the variant with nonspecific orders, known to be equivalent to the problem in which the time windows can be ordered by time, we also show equivalence to the basic lot-sizing problem with upper bounds on the stocks. Here we derive polynomial time dynamic programming algorithms and tight extended formulations for the uncapacitated and constant capacity problems with general costs. For the problem with delivery time windows, we use a similar approach to derive tight extended formulations for both the constant capacity and uncapacitated problems with Wagner-Whitin (non-speculative) costs.

Scheduling tank container movements for chemical logistics

AbstractEffective logistics is the key to improving supply chain performance. Tank containers are attractive from the viewpoints of safety, cost, and environment, and are widely used for transporting fluid chemicals. Minimizing the logistics costs arising from the container flow imbalances across the globe and container cleaning is a major issue that chemical companies and affiliated third‐party logistics firms face routinely. In contrast to dry containers, this important problem of managing tank containers in global chemical logistics has received no attention. An innovative, event‐based, “pull” approach is presented for the minimum‐cost or the maximum‐profit scheduling of the transport and cleaning of multiproduct tank containers (loaded and empty) given a set of projected shipment orders. A novel linear programming formulation is developed and illustrated through examples that successfully solves large, industrially relevant problems with key practical considerations such as alternate ship schedules, delivery time windows, and intermodal transport routes. © 2004 American Institute of Chemical Engineers AIChE J, 51: 178–197, 2005

A Two-Echelon Inventory Optimization Model with Demand Time Window Considerations

This paper studies a two-echelon dynamic lot-sizing model with demand time windows and early and late delivery penalties. The problem is motivated by third-party logistics and vendor managed inventory applications in the computer industry where delivery time windows are typically specified under a time definite delivery contract. Studying the optimality properties of the problem, the paper provides polynomial time algorithms that require O(T 3) computational complexity if backlogging is not allowed and O(T 5) computational complexity if backlogging is allowed.

Multiple crossdocks with inventory and time windows

Crossdocking studies have mostly been concerned with the physical layout of a crossdock or on a single crossdock. In this work, we study a network of crossdocks taking into consideration delivery and pickup time windows, warehouse capacities and inventory-handling costs. Because of the complexity of the problem, local search techniques are developed and used with simulated annealing and tabu search heuristics. Extensive experiments were conducted and results show that the heuristics outperform CPLEX, providing solutions in realistic timescales.

Warehouse space capacity and delivery time window considerations in dynamic lot-sizing for a simple supply chain

This paper studies a single item, two-echelon dynamic lot-sizing model with delivery time windows, early shipment penalties, and warehouse space capacity constraints. The two-echelon system consists of a warehouse and a distribution center. The underlying problem is motivated by third party logistics and vendor managed inventory applications in the computer industry where delivery time windows are typically specified by the distribution center under the terms of a supply contract. The capacity of the warehouse is limited. This constraint should be considered explicitly because the finished products are expensive items (such as computer equipment and peripherals), and they have to be stored in the warehouse in an appropriate climate before they are shipped to the distribution center. Studying the optimality properties of the problem, the paper provides a polynomial time algorithm for computing its solution. The optimal solution includes: (i) the replenishment plan specifying “when, and in what quantities, to replenish the stock at the third-party warehouse,” and (ii) the dispatch plan specifying “when, and in what quantities, to release an outbound shipment to the distribution center, and in which order to satisfy the demands.” The algorithm is based on dynamic programming and requires O( T 3) computational complexity.

Solving a Practical Pickup and Delivery Problem

We consider a pickup and delivery vehicle routing problem commonly encountered in real-world logistics operations. The problem involves a set of practical complications that have received little attention in the vehicle routing literature. In this problem, there are multiple carriers and multiple vehicle types available to cover a set of pickup and delivery orders, each of which has multiple pickup time windows and multiple delivery time windows. Orders and carrier/vehicle types must satisfy a set of compatibility constraints that specify which orders cannot be covered by which carrier/vehicle types and which orders cannot be shipped together. Order loading and unloading sequence must satisfy the nested precedence constraint that requires that an order cannot be unloaded until all the orders loaded into the truck later than this order are unloaded. Each vehicle trip must satisfy the driver's work rules prescribed by the Department of Transportation which specify legal working hours of a driver. The cost of a trip is determined by several factors including a fixed charge, total mileage, total waiting time, and total layover time of the driver. We propose column generation based solution approaches to this complex problem. The problem is formulated as a set partitioning type formulation containing an exponential number of columns. We apply the standard column generation procedure to solve the linear relaxation of this set partitioning type formulation in which the resulting master problem is a linear program and solved very efficiently by an LP solver, while the resulting subproblems are computationally intractable and solved by fast heuristics. An integer solution is obtained by using an IP solver to solve a restricted version of the original set partitioning type formulation that only contains the columns generated in solving the linear relaxation. The approaches are evaluated based on lower bounds obtained by solving the linear relaxation to optimality by using an exact dynamic programming algorithm to solve the subproblems exactly. It is shown that the approaches are capable of generating near-optimal solutions quickly for randomly generated instances with up to 200 orders. For larger randomly generated instances with up to 500 orders, it is shown that computational times required by these approaches are acceptable.

Increasing the cost efficiency of e‐fulfilment using shared reception boxes

Recent research into last mile e‐grocery logistics has revealed that goods reception mode is one of the key issues for the operational efficiency of home deliveries. Hitherto, the research has considered home delivery concepts using attended reception and concepts enabling unattended reception based on customer‐specific reception boxes and delivery boxes. Customer‐specific reception boxes are installed in the consumer’s home yard or garage, while delivery boxes are insulated boxes that are returned to the retailer. Focuses on a third possible concept for unattended deliveries, namely shared reception boxes. Due to shared usage, the utilisation level of the facility is higher than in the case of customer‐specific unattended reception concepts. Analyses the operational cost levels of home delivery concepts using both attended and unattended reception, using real point‐of‐sales data and vehicle routing tools. The results show that transportation costs using the shared reception box concept are 55‐66 per cent lower in comparison with the current standard concept with attended reception and two‐hour delivery time windows. On the basis of our analysis, the cost reduction alone justifies the two‐to‐five‐year payback period of the investment required, even if there is only a fairly small number of deliveries per day. Surprisingly, the payback period is longer when customer density increases.

Specification for a dynamic vehicle routing and scheduling system

Abstract In an e-commerce environment, order fulfilment is driven by customer demands and expectations. A dynamic vehicle routing and scheduling system may be specified which allows e-commerce customers to select their own delivery Time Windows and have these confirmed on-line as they place their order. The methodology is based upon demand forecasting, which leads to the generation of phantom orders and phantom routes. Subsequently, actual orders substitute for phantom orders in an on-line customer order process. The routing and scheduling method includes using both parallel tour-building and parallel insertion algorithms. Customer service levels are confirmed using GPS tracking and tracing, and a feedback loop uses expert systems or artificial intelligence as an input to the demand forecasting data to restart the whole process.

Can Online Grocers Deliver?: Some Logistics Considerations

The logistics and distribution factors that play a role in the commercial viability of online grocers, and the level of service delivered to customers, are considered. The two business operation models studied are the pureplay model in which the grocer handles the entire shopping experience, and the multichannel model, in which the grocer combines the convenience of online shopping with the stability and leverage of brick-and-mortar stores. The trade-offs that exist for specific delivery policies associated with each type of model are examined. Factors that influence trade-offs are highlighted and include number of demands, number of depots, number of vehicles at each depot, duration of time windows, and road network topology. The commercial viability of each model is examined, and sensitivity analysis to the total demand under different logistical factors is performed. The results illustrate the root causes for the difficult times experienced by this segment of the business-to-consumer electronic commerce sector. Providing the high level of service and convenience (in the form of specific and tight delivery time windows) desired by online customers often results in higher delivery costs, which directly affect the profitability of the operation.

Identifying the success factors in e‐grocery home delivery

Efforts in the electronic grocery shopping, i.e. e‐grocery business, focus especially on the physical distribution of the goods. For example, in the USA there are several e‐grocery service providers with various operating concepts and offering various service levels. The home delivery concept of Streamline is based on a reception box at the customer’s garage or home yard enabling unmanned reception. In contrast, WebVan has launched a home delivery concept where the customer can select a convenient half an hour delivery time window. Various service concepts have been implemented and offered, but has anyone really analysed the differences in cost structures of these two and of other concepts in between the two extremes? Investigates existing home delivery service concepts from different angles and presents concrete simulation results of various parameters representing several home delivery service levels. Eventually, identifying the parameters will give guidelines for the future development of the e‐grocery home delivery services.

Optimisation of introducing foreign genes into egg cells and zygotes of wheat (Triticum aestivum L.) via microinjection

An expeditious and highly efficient technique of microinjection has been developed with the aim of introducing exogenous DNA into egg cells and zygotes of wheat. Using a mechanical-dissection method and a novel immobilisation approach enabled us to microinject around 15 egg cells of wheat per hour. Exposing the protoplasts to a high-frequency alternating-current field for immobilisation, a significantly higher transient expression rate of the injected genes (46% and 52% for egg cells and zygotes, respectively) could be achieved than reported thus far for plant protoplasts. Whether this high transformation efficiency is due to the highfrequency electrical field applied for immobilising the protoplasts is not known. The transformation rate appeared to be a factor depending upon the time of egg cell isolation. According to the ultrastructural observations this seems to reflect a variation in competence of the egg cells during in situ development. In order to conduct studies directed towards establishing the optimal timewindow for DNA delivery into the fertilised egg cell, the time course of DNA dynamics during zygotic development has been quantified via quantitative microspectrofluorometry.

On-Line Algorithms for Truck Fleet Assignment and Scheduling Under Real-Time Information

With greater availability of real-time information systems, algorithms are needed to support commercial fleet operators in their decisions to assign vehicles and drivers to loads in a dynamic environment. A rolling horizon framework for the dynamic assignment and sequencing of trucks to jobs consisting of picking up and delivering full truckloads when requests for service arise on a continuous basis is presented. A mathematical formulation of the problem faced at each stage is presented; its solution allows for the dynamic reassignment of trucks to loads, including diversion to a new load of a truck already en route to pick up another load, as well as for the dynamic resequencing of the order in which loads are to be served as new loads arrive and conditions unfold. Loads have associated time windows for pickup and delivery, and the objective function includes an explicit penalty cost for not serving a particular load. A solution algorithm is presented and implemented, and computational results are presented, yielding insight into various operational trade-offs in dynamic fleet operations. Because applicability of the solution algorithm is limited to relatively small problems, and given the stochastic dynamic nature of these systems, numerical experiments are performed to compare the quality of the solution obtained using this approach with the performance of simpler and less computationally demanding local rules.

A tabu search algorithm for the multi-trip vehicle routing and scheduling problem

This paper describes a novel tabu search heuristic for the multi-trip vehicle routing and scheduling problem (MTVRSP). The method was developed to tackle real distribution problems, taking into account most of the constraints that appear in practice. In the MTVRSP, besides the constraints that are common to the basic vehicle routing problem, the following ones are present: during each day a vehicle can make more than one trip; the customers impose delivery time windows; the vehicles have different capacities considered in terms of both volume and weight; the access to some customers is restricted to some vehicles; the drivers' schedules must respect the maximum legal driving time per day and the legal time breaks; the unloading times are considered.

Uterine rupture after previous cesarean delivery: Maternal and fetal consequences

The purpose of this study was to identify the risk factors associated with overt, catastrophic uterine rupture and to report maternal and neonatal outcomes. The associated elapsed time window for delivery of an uncompromised neonate was also investigated. A retrospective study with review of charts and monitor strips was performed. Between Jan. 1, 1983, and June 30, 1992, there were 106 cases of uterine rupture at our institution. Of these, seven charts were incomplete and excluded; of the remainder, 28 patients had complete, 13 patients had partial, and 58 patients had no fetal extrusion into the maternal abdomen. Maternal characteristics or intrapartum events were not predictive of the catastrophic extent of uterine rupture. There was one maternal death. Complete fetal extrusion was associated with a higher incidence of perinatal mortality and morbidity. Significant neonatal morbidity occurred when > or = 18 minutes elapsed between the onset of prolonged deceleration and delivery. Neonatal and maternal complications in uterine rupture with complete fetal extrusion were low with prompt intervention.