Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2003. / Includes bibliographical references (p. 109-111). / Distribution and pricing strategies play a central role in the field of supply chain management. Heuristic approaches to the vehicle routing problem (VRP) are usually used to design optimal delivery routes to serve geographically dispersed customers, who are price elastic. There is a rich literature discussing either the manufacturer's distribution strategy or its pricing initiatives. The purpose of this thesis is to develop a profit maximization model that presents an integrated distribution and pricing strategy for any company facing such issues. We first examine a simplified scenario when all customers are located in the same delivery region and their demand is deterministic. Both truckload (TL) and less-than-truckload (LTL) shipment strategies are analyzed and compared. We later extend our findings to multiple delivery regions and discuss the impact of the manufacturer's pricing flexibility on its profit. Then we relax the assumption of deterministic customer demand and introduce the safety stock cost. Finally the application on across delivery region situations is shown. Although some of our assumptions simplify our model, we believe that it provides insight into more complex supply chain management problems. / by Ye Mao. / S.M.

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2002. / "September 2002." / Includes bibliographical references (p. 96-97). / by Raphael Avram Schorr. / S.M. / M.Eng.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center , 2002. / Includes bibliographical references (p. 185-187). / by Seong-Cheol Kang. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Operations Research Center, 2004. / Includes bibliographical references (p. 143-146). / This thesis considers tlhe problem of routing in a network where the travel times along the arcs are modeled as independent random variables. A standard approach to routing in such networks is to select a path with the least expected travel time. One of the problems with this approach is that it does not take into consideration factors such as the travel time variance. Additionally. such an approach implicitly assumes each user in the network has the same routing objective. In this thesis we develop an approach to routing in probabilistic networks in which these problems are addressed. The fundamental concept in our approach is that, for a given user with a set of routing options at a given node. we approximate the distributions of travel time for these options. Using these approximate distributions, the options are compared according to a user-specified routing objective, and the best option is selected. The primary benefit of this approach is that one is not limited to a particular routing objective as the computed distributions of travel time allow us to efficiently determine an effective routing option for a arbitrary routing objective that depends on factors of random travel time other than the mean. The distribution of travel time adopted in this thesis is the minimum travel time probability distribution. which is the distribution of travel time over all fastest paths. In a class of networks termed as series-parallel networks. the minimum travel time distribution can be calculated efficiently. / (cont.) For general, non-series-parallel networks. the approximation we adopt is the minimum travel time distribution obtained from a related series-parallel network. The performance and the benefits of this approach to routing are illustrated on three networks. The numerical results are obtained using an efficient implementation of the algorithms proposed in this thesis. We also consider the problem of generating an acyclic graph from a cyclic graph, and we propose a data structure that allows for the efficient calculation of the sum and minimum of independent random variables. / by Jonathan Ramsay Key. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2006. / Page 133 blank. / Includes bibliographical references (p. 131-132). / A prototype tool was developed to support the planning of ground delay programs (GDPs) under uncertainty. Planned hours in advance, GDPs are subject to significant arrival capacity uncertainty, which reduces their efficacy in defraying the high cost of airborne delays. The tool addresses this uncertainty by using a set of different possible arrival capacity profile forecasts and modeling the outcome of the program under each forecast. A variety of different metrics are developed based on these results, including both system-wide and flight specific forecasts of queue size and the evolution of delay over time. To allow air and ground delay to be considered simultaneously, a cost function that takes both into account is proposed. The tool also addresses the dynamic nature of a GDP by allowing the traffic manager to set a system time variable and model possible future decisions. Taken a step further, these projections can be used as part of a two-step model, which evaluates a program under the assumption that a traffic manager will revise the GDP at a later time, once additional information regarding arrival capacity forecasts has become available. Revising a program can significantly reduce its expected cost, but different programs may not respond in the same way to future revision and are likely to exhibit differing magnitudes of expected cost reduction. In fact, the best initial decision may be one that trades initial cost for the ability to revise the program more effectively in the future. / by Michael John Hanowsky. / S.M.

Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 113). / The Last Mile Problem (LMP) refers to the provision of travel service from the nearest public transportation node to a home or office. We study the supply side of this problem in a stochastic setting, with batch demands resulting from the arrival of groups of passengers at rail stations or bus stops who request last-mile service. Closed-form bounds and approximations are derived for the performance of Last Mile Transportations Systems as a function of the fundamental design parameters of such systems. An initial set of results is obtained for the case in which a fleet of vehicles of unit-capacity provides the Last Mile service and each delivery route consists of a simple round-trip between the rail station and bus stop and the single passenger's destination. These results are then extended to the general case in which the capacity of a vehicle is an arbitrary, but typically small (under 10) number. It is shown through comparisons with simulation results, that a particular strict upper bound and an approximate upper bound, both derived under similar assumptions, perform consistently and remarkably well for the entire spectrum of input values and conditions simulated. These expressions can therefore be used for the preliminary planning and design of Last Mile Transportation Systems, especially for determining approximately resource requirements, such as the number of vehicles/servers needed to achieve some pre-specified level of service. / by Hai Wang. / S.M. / S.M.in Transportation

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2003. / Includes bibliographical references (p. 129). / Most air traffic delay measures assess delays relative to schedule. Over the past decades, however, airline schedules have been adjusted to take into account airspace congestion and yield better on-time performance. In that context, delay measures that are using scheduled times as a benchmark are of very limited use in assessing airport and airspace system congestion, since delay has already been built into the schedule. The primary goal of this thesis is to develop a measure that will estimate "true" delays that are not sensitive to schedule adjustments. In order to calculate "true" delays, we compute the difference between the actual gate-to-gate time and a theoretical benchmark, the "baseline". The baseline time to be used is O-D specific and is defined here as the gate-to-gate time from origin to destination under optimal (non-congested) conditions. We choose the fifteenth percentile of reported statistics on gate-to-gate time as an estimator of the baseline. We then compute baseline times for 618 major O-D pairs. Using the baseline times, we compute "true delays" on these 618 O-D pairs and observe that they are about 40% to 60% larger than delays relative to schedule. We also develop two methods to attribute O-D delays to the origin and destination airports. Using these methods, we determine that airports incurred about 5 to 13 minutes of delay per operation in 2000, depending on the airport under consideration. Airport rankings according to "true" delays are compared to airport rankings obtained from OPSNET delay statistics. The comparison suggests that, although OPSNET statistics underestimate the magnitude of delays, they yield very comparable airport rankings and can therefore be used to rank airports with respect to congestion. Finally, we change perspective and look at the development of probabilistic models for designing flight schedules that minimize delays relative to schedule. We use the simple case of an airline scheduling an aircraft for a round trip to illustrate the complexities and uncertainties associated with optimal scheduling. / by Yasmine E. Alj. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Operations Research Center, 2004. / Includes bibliographical references (p. 87-89). / Major airlines aim to generate schedules that maximize profit potential and satisfy constraints involving flight schedule design, fleet assignment, aircraft maintenance routing and crew scheduling. Almost all aircraft and crew schedule optimization models assume that flights, aircraft, crews, and passengers operate as planned. Thus, airlines typically construct plans that maximize revenue or minimize cost based on the assumption that every flight departs and arrives as planned. Because flight delays and cancellations result from numerous causes, including severe weather conditions, unexpected aircraft and crew failures, and congestion at the airport and in the airspace, this deterministic, optimistic scenario rarely, if ever, occurs. In fact, schedule plans are frequently disrupted and airlines often incur significant costs in addition to those originally planned. To address this issue, an approach is to design schedules that are robust to schedule disruptions and attempt to minimize realized, and not planned, costs. In this research, we review recovery approaches and robustness criteria in the context of airline schedule planning. We suggest new approaches for designing fleet assignments that facilitate recovery operations, and we present models to generate plans that allow for more robust crew operations, based on the idea of critical crew connections. We also examine the impact on robustness of new scheduling practices to debank hub airports. / by Claudine Biova Agbokou. / S.M.

Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2015. / Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2015. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 107-109). / With the continuous growth in international container shipping, many container terminals in maritime ports face congestion, particularly during peak hours of service, and when there is limited space in the storage area. Thus, there has been increasing interest in improving operations efficiency in container terminals. An efficient terminal, in general, is one that discharges containers from the ships in a timely manner and delivers containers to customers with a reasonable wait time. Moreover, a key performance measure in the storage area is the number of moves performed by yard cranes. Due to limited space in the storage area, containers are stacked on top of each other, forming a column of containers that can be accessed by yard cranes only from the top. Therefore, in order to retrieve a container that is covered by other containers, the blocking containers must be relocated to other slots. Because such relocation moves are costly for the port operators and result in service delays, one of the main challenges in the storage area is to plan the moves such that the number of relocations is minimized. This problem is referred to as the Container Relocation Problem (CRP). The CRP in its most simplified setting is concerned with finding a sequence of moves that retrieves all containers in a pre-defined order with a minimum number of relocations, assuming that no new containers are stacked during the retrieval process. Also, it is often assumed that the non-blocking containers cannot be relocated (i.e., repositioning moves are not allowed), an assumption that can result in a sub-optimal solution. Other variants of the container relocation problem include the dynamic CRP and the CRP with incomplete information. The former involves minimizing the number of relocations when containers are continuously stacked in and retrieved from the storage area, and the latter refers to the case that the departure times of containers are not fully known in advance. For example, a probabilistic distribution of container departure orders, or approximate departure times (in the form of time windows) might be known. Another important efficiency metric, in addition to the number of relocations, is customer wait times during the retrieval process. In particular, when repositioning moves are allowed in the system, there is a trade-off between the total number of relocations (including repositionings) and wait times, because such repositioning moves make the retrieval process faster for trucks arriving in the future. Also, it might be desired to prioritize some customers so that those prioritized experience shorter wait times. For example, in terminals with appointment systems, shorter waiting time guarantees can be given to customers who book in advance a time slot for picking up their containers. In this thesis, we propose optimization models that capture service-based and cost-based objectives and study different service policies. In the first part of this thesis, we study the CRP with complete information using an optimization model and heuristic approach. In particular, we formulate CRP (with no restrictive assumptions on repositioning moves) as an Integer Program that minimizes the weighted sum of the number of relocations and the total wait time of customers. Our integer program provides the optimal sequence of moves for retrieving containers subject to various service policies. For example, it can be used by port operators to minimize customer wait times, or to give different waiting time guarantees to different customers to reflect relative priorities. Moreover, by assigning different weight factors to the two objectives, one can use our model to plan repositioning moves. We also extend our model to the dynamic CRP and illustrate how the flexibility in the stacking process can be exploited to optimize jointly the sequence of moves and the stacking position of containers. Additionally, we propose a class of flexible retrieval policies. We demonstrate that flexible policies can result in fewer relocations and shorter wait times, thereby benefiting both the port operators and customers. In the second part of this thesis, we study the CRP with incomplete information in a 2-stage setting where the departure times of a subset of containers are initially known and the departure times of other containers are revealed at once at a later time. The contributions are twofold. First, we propose an approximate stochastic optimization algorithm, called ASA*, which is a branch-and-bound framework combined with a sampling technique, and to the best of our knowledge is the first optimization algorithm proposed for this problem. We provide theoretical bounds on the approximation errors and present numerical results showing the computational tractability and efficiency of our algorithm. Second, we use the ASA* algorithm and a myopic heuristic to study the value of information, that is, the effect of the number of containers initially known on the number of relocations. In the last part of this thesis, we introduce a simulator that is capable of integrated simulation of port operations, including the retrieval process, the stacking process, and other aspects such as allocating cranes to containers and allocating trucks to cranes. Our simulator captures the practical details of operations that cannot be modelled in an optimization framework and is capable of simulating long periods (e.g. a week) of realistic-scale operations. / by Setareh Borjian Boroujeni. / S.M. in Transportation / S.M.

Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2010. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (p. 201-209). / The broad goal of this thesis is to demonstrate the potential positive impacts of applying automatic data to the management and tactical planning of a modern urban railway. Tactical planning is taken here to mean the set of transport-specific analysis and decisions required to manage and improve a railway with time horizons measured in weeks, months, or up to a year and little or no capital investment requirements. This thesis develops and tests methods to (i) estimate on-train loads from automatic measurements of train payload weight, (ii) estimate origin-destination matrices by combining multiple types of automatic data, (iii) study passenger incidence (station arrival) behavior relative to the published timetable, (iv) characterize service quality in terms of the difference between automatically measured passenger journey times and journey times implied by the published timetable. It does so using (i) disaggregate journey records from an entry- and exit-controlled automatic fare collection system, (ii) payload weight measurements from "loadweigh" sensors in train suspension systems, and (iii) aggregate passenger volumes from electronic station gatelines. The methods developed to analyze passenger incidence behavior and service quality using these data sources include new methodologies that facilitate such analysis under a wide variety of service conditions and passenger behaviors. The above methods and data are used to characterize passenger demand and service quality on the rapidly growing, largely circumferential London Overground network in London, England. A case study documents how a tactical planning intervention on the Overground network was influenced by the application of these methods, and evaluates the outcomes of this intervention. The proposed analytical methods are judged to be successful in that they estimate the desired quantities with sufficient accuracy and are found to make a positive contribution to the Overground's tactical planning process. It is concluded that relative measures of service quality such as the one developed here can be used in cross-sectional analysis to inform tactical planning activity. However, such measures are of less utility for longitudinal evaluation of tactical planning interventions when the basis against which service quality is judged (in this case the timetable) is changed. Under such circumstances, absolute measures, such as total observed passenger journey times, should be used as well. / by Michael S. Frumin. / S.M. / S.M.in Transportation