A robust optimization approach to dispatching technicians under stochastic service times

We consider the problem of dispatching technicians to service/repair geographically distributed equipment. This problem can be cast as a vehicle routing problem with time windows, where customers expect fast response and small delays. Estimates of the service time, however, can be subject to a significant amount of uncertainty due to misdiagnosis of the reason for failure or surprises during repair. It is therefore crucial to develop routes for the technicians that would be less sensitive to substantial deviations from estimated service times. In this paper we propose a robust optimization model for the vehicle routing problem with soft time windows and service time uncertainty and solve real-world instances with a branch and price method. We evaluate the efficiency of the approach through computational experiments on real industry routing data.     

A time–space network based exact optimization model for multi-depot bus scheduling

The vehicle scheduling problem, arising in public transport bus companies, addresses the task of assigning buses to cover a given set of timetabled trips with consideration of practical requirements, such as multiple depots and vehicle types as well as depot capacities. An optimal schedule is characterized by minimal fleet size and minimal operational costs including costs for unloaded trips and waiting time. This paper discusses the multi-depot, multi-vehicle-type bus scheduling problem (MDVSP), involving multiple depots for vehicles and different vehicle types for timetabled trips. We use time–space-based instead of connection-based networks for MDVSP modeling. This leads to a crucial size reduction of the corresponding mathematical models compared to well-known connection-based network flow or set partitioning models. The proposed modeling approach enables us to solve real-world problem instances with thousands of scheduled trips by direct application of standard optimization software. To our knowledge, the largest problems that we solved to optimality could not be solved by any existing exact approach. The presented research results have been developed in co-operation with the provider of transportation planning software PTV AG. A software component to support planners in public transport was designed and implemented in context of this co-operation as well.     

A fuzzy clustering approach to real-time demand-responsive bus dispatching control

Quick response (QR) to passenger needs is a key objective for advanced public transportation systems (APTS), and it has become increasingly important for contemporary metropolitan bus operations to gain a competitive advantage over private transportation. This paper presents a real-time control methodology for demand-responsive bus operations that respond quickly to passenger needs. The proposed method primarily involves two levels of functionality: (1) short-term forecasting of passenger demands using time-series prediction models, and (2) identification of service strategies coupled with the associated bus service segments using fuzzy clustering technologies in response to variances in passenger demand attributes and traffic conditions. The proposed bus operations method identifies the demand-responsive vehicle service strategies primarily according to the predicted up-to-date attributes of passengers’ demands, rather than deterministic passenger arrival rates, which were generally used in previous literature. In addition, the variation of traffic conditions along bus lines is considered in the proposed method. Results from numerical studies using real data of passengers’ demands, including passenger volume at each bus stop and the passenger origin-destination (O-D) patterns, are presented to demonstrate the effectiveness of the proposed method for real-world applications.     

A multicriteria approach for optimizing bus schedules and school starting times

In many rural counties pupils on their way to school are a large, if not the largest group of customers for public mass transit. Hence an effective optimization of public mass transit in these regions must include the traffic caused by pupils. Besides a change in the schedules of the buses and the starting times of the trips, the school starting time may become an integral part of the planning process. We discuss the legal framework for this optimization problem in German states and counties and present a multi-objective mixed-integer linear programming formulation for the simultaneous specification of school and trip starting times. For its solution, we develop a two-stage decomposition heuristic and apply it to practical data sets from three different rural German counties.     

A mathematical programming model for the bus deviation route problem

In small towns, or in those peripherical metropolitan areas in which the demand for public transportation is relatively low, the objectives of the bus route planner are different from those faced in highly congested networks. Some towns, also in Italy, are experimenting with urban public transportation systems where regular bus routes are designed which allow users located at specific points outside the main line to signal their presence to the bus driver, who then deviates from the main route to satisfy this demand. This way the bus line is a mixture between a regular line and a dial-a-ride system. The bus deviation route problem is concerned with the design problem which arises in planning the location of the demand points outside the line. A model is presented which takes into account both the advantage of passengers served by this deviation device and the disadvantage suffered by passengers on the bus, whose travel time increases during deviations, and by passengers downstream of the deviation whose waiting time also increases. Through some modeling assumption we are able to represent this problem as a mixed integer linear programming problem, whose relatively low dimension allows for exact solution through standard simplex-based branch and bound code. The proposed model has been applied to a real case and some results of this are presented and discussed.     

A two-scale model for the periodic homogenization of the wave equation

We present a new mathematical object designed to analyze the oscillations occurring on both microscopic and macroscopic scales in a wave equation with oscillating coefficients and data. Through a Bloch wave homogenization method, our study addresses typical problems of two-scale convergence in the interior of the domain, and sheds some light on the behavior near the boundary. A decoupled system of (systems of) transport equations is derived in each energy band, and the total energy field is approximated. We also recover previously known results in homogenization as a restricted part of our model.     

A stochastic model for drilling optimization

Drilling optimization problems in oilfields are usually formulated and solved by using deterministic mathematical models, in which uncertain (indeterminate) factors or random issues are not taken into consideration. However, it has been widely experienced that random factors (such as those from soil layers, drill bits, and surface equipment) greatly affect the drilling performance. This paper introduces a new stochastic model for describing such random effects. This model, when used to optimization design, is more practical and provides a better characterization for real oilfield situations as compared with other deterministic models, and has been demonstrated to be more efficient in solving real design problems of drilling optimizations.     

A theoretical model of interpurchase times

A theoretical model of interpurchase times at the individual level is developed. This model provides a bench-mark for the expected regularity of a product's purchase cycle in the absence of any confounding external marketing activity. Products which empirically deviate from the theoretical expectations can then be further studied to determine the causes of the deviations. The theoretical model also tests the robustness of the assumption of a gamma distribution at the individual level, an assumption which is frequently made in the marketing literature.     

A model for assisted periodic breathing with degenerate permeability

The process of breathing is interpreted as forced periodic motion of a viscoelastic deformable porous medium with gas exchange between the interior and exterior, driven by forces acting on its boundary. Energy and mass are supplied to the system by muscle activity, and also possibly by external ventilation in case of assisted breathing for patients with lungs insufficiency. Hysteresis in the pressure–volume characteristic and possible degeneracy of the pressure-dependent terms are also taken into account. The main result consists in proving the existence of a periodic solution under arbitrary periodic forcing in suitable function spaces.     

Two critical times for the SIR model

We consider the SIR model and study the first time the number of infected individuals begins to decrease and the first time this population is below a given threshold. We interpret these times as functions of the initial susceptible and infected populations and characterize them as solutions of a certain partial differential equation. This allows us to obtain integral representations of these times and in turn to estimate them precisely for large populations.     

Perturbation theory for the periodic Anderson model

We investigate the system of conductivity electrons and f-localized electrons described by the periodic Anderson model. Single-site hybridization of the state of two constituent subsystems of electrons is treated as a perturbation. We develop a new diagram technique based on the use of multiparticle one-site irreducible Green’s functions for the f-electrons and the standard Wick theorem for the subsystem of conductivity electrons. We derive the Dyson equations for the one-particle Green’s functions and find the relation between these functions. These results are exact and can be used as a starting point for self-consistent approximations. In the Hubbard-I approximation, we analyze the spectrum of one-particle perturbations. Translated from Teoreticheskaya i Matematicheskaya Fizika, Vol. 110, No. 2, pp. 308–322, February, 1997.     

A compact optimization model for the tail assignment problem

This paper investigates a new model for the so-called Tail Assignment Problem, which consists in assigning a well-identified airplane to each flight leg of a given flight schedule, in order to minimize total cost (cost of operating the flights and possible maintenance costs) while complying with a number of operational constraints. The mathematical programming formulation proposed is compact (i.e., involves a number of $0?1$ decision variables and constraints polynomial in the problem size parameters) and is shown to be of significantly reduced dimension as compared with previously known compact models. Computational experiments on series of realistic problem instances (obtained by random sampling from real-world data set) are reported. It is shown that with the proposed model, current state-of-the art MIP solvers can efficiently solve to exact optimality large instances representing 30-day flight schedules with typically up to 40 airplanes and 1500 flight legs connecting as many as 21 airports. The model also includes the main existing types of maintenance constraints, and extensive computational experiments are reported on problem instances of size typical of practical applications.     

A periodic cointegration model of quarterly consumption

A periódic cointegration model is proposed to describe quarterly observed consumption. This model allows the cointegrating vectors and the adjustment parameters to vary with the seasons. Its links are discussed with an often considered standard economic theoretical model for macroeconomic variables like consumption. A simple empirical model specification strategy is given and applied to Austrian consumption and income data.     

A model for setting services on auxiliary bus lines under congestion

In this paper, a mathematical programming model and a heuristically derived solution is described to assist with the efficient planning of services for a set of auxiliary bus lines (a bus-bridging system) during disruptions of metro and rapid transit lines. The model can be considered static and takes into account the average flows of passengers over a given period of time (i.e., the peak morning traffic hour). Auxiliary bus services must accommodate very high demand levels, and the model presented is able to take into account the operation of a bus-bridging system under congested conditions. A general analysis of the congestion in public transportation lines is presented, and the results are applied to the design of a bus-bridging system. A nonlinear integer mathematical programming model and a suitable approximation of this model are then formulated. This approximated model can be solved by a heuristic procedure that has been shown to be computationally viable. The output of the model is as follows: (a) the number of bus units to assign to each of the candidate lines of the bus-bridging system; (b) the routes to be followed by users passengers of each of the origin–destination pairs; (c) the operational conditions of the components of the bus-bridging system, including the passenger load of each of the line segments, the degree of saturation of the bus stops relative to their bus input flows, the bus service times at bus stops and the passenger waiting times at bus stops. The model is able to take into account bounds with regard to the maximum number of passengers waiting at bus stops and the space available at bus stops for the queueing of bus units. This paper demonstrates the applicability of the model with two realistic test cases: a railway corridor in Madrid and a metro line in Barcelona.     

Topology optimization of periodic Mindlin plates

Periodic structures exhibit unique dynamic characteristics that make them act as tunable mechanical filters for wave propagation. As a result, waves can propagate along the periodic structures only within specific frequency bands called the ‘pass bands’ and wave propagation is completely blocked within other frequency bands called the ‘stop bands’ or ‘band gaps’. The spectral width of these bands can be optimized using topology optimization. In this paper, topology optimization is used to maximize the fundamental natural frequency of Mindlin plates while enforcing periodicity. A finite element model for Mindlin plates is presented and used along with an optimization algorithm that accounts for the periodicity constraint in order to determine the optimal topologies of plates with various periodic configurations. The obtained results demonstrate the effectiveness of the proposed design optimization approach in generating periodic plates with optimal natural frequency and wide stop bands. The presented approach can be invaluable design tool for many structures in order to control the wave propagation in an attempt to stop/confine the propagation of undesirable disturbances.     

A quadratic programming model for product configuration optimization

The various features of any product are differentially appealing to the various portions of the consumer population and have differential costs of production and marketing. This paper considers the problem of “overall product optimization”, or more specifically, “optimal product configuration”. Product price is, of course, a part of this configuration.     

A multi-criteria optimization model for humanitarian aid distribution

Natural disasters are phenomenons which strike countries all around the world. Sometimes, either by the intensity of the phenomenon or the vulnerability of the country, help is requested from the rest of the world and relief organizations respond by delivering basic aid to those in need. Humanitarian logistics is a critical factor in managing relief operations and, in general, there is a lack of attention on the development of mathematical models and solution algorithms for strategic and tactical decisions in this area. We acknowledge that in humanitarian logistics traditional cost minimizing measures are not central, and postulate that other performance measures such as time of response, equity of the distribution or reliability and security of the operation routes become more relevant. In this paper several criteria for an aid distribution problem are proposed and a multi-criteria optimization model dealing with all these aspects is developed. This model is the core of a decision support system under development to assist organizations in charge of the distribution of humanitarian aid. Once the proposed criteria and the model are described, an illustrative case study based on the 2010 Haiti catastrophic earthquake is presented, showing the usefulness of the proposal.     

A note on global attractivity of the periodic solution for a model of hematopoiesis

For the generalized periodic model of hematopoiesis $x^{\prime }\left(t\right)=-a\left(t\right)x\left(t\right)+\sum _{i=1}^m\frac{b_i\left(t\right)}{1+x{(t-{\tau }_i\left(t\right))}^n},$ with $0<n\le 1$, sufficient conditions for the global attractivity of its positive periodic solution are given, improving previous results in the literature. The effectiveness of the present criterion is illustrated by a numerical example.     

A metaheuristic for the school bus routing problem with bus stop selection

Existing literature on routing of school buses has focused mainly on building intricate models that attempt to capture as many real-life constraints and objectives as possible. In contrast, the focus of this paper is on understanding the joint problem of bus route generation and bus stop selection – two important sub-problems – in its most basic form. To this end, this paper defines the school bus routing problem (SBRP) as a variant of the vehicle routing problem in which three simultaneous decisions have to be made: (1) determine the set of stops to visit, (2) determine for each student which stop (s)he should walk to, and (3) determine routes that lie along the chosen stops, so that the total traveled distance is minimized. An MIP model of this basic problem is developed.