A time minimising transportation problem with quality dependent time

The usual assumption made in time minimising transportation problem is that the time for transporting a positive amount in a route is independent of the actual amount transported in that route. In this paper we make a more general and natural assumption that the time depends on the actual amount transported. We assume that the time function for each route is an increasing piecewise constant function. Four algorithms - (1) a threshold algorithm, (2) an upper bounding technique, (3) a primal dual approach, and (4) a branch and bound algorithm - are presented to solve the given problem. A method is also given to compute the minimum bottle-neck shipment corresponding to the optimal time. A numerical example is solved illustrating the algorithms presented in this paper.     

The single machine total weighted completion time scheduling problem with the sum-of-processing time based models: Strongly NP-hard

Although the single machine scheduling problem to minimize the total weighted completion times with the sum-of-processing time based learning or aging effects have been known for a decade, it is still an open question whether these problems are strongly NP-hard. We resolve this issue and prove them to be strongly NP-hard with the learning effect as well as with the aging effect. Furthermore, we construct an exact parallel branch and bound algorithm for the problem with general sum-of-processing time based models, which can solve optimally moderate problem instances in reasonable time.     

Diffeomorphisms as time one maps

Summary. We investigate the inverse ODE problem of finding a vector field such that the time one map associated to its flow coincides with a given diffeomorphism. Using a constructive approach we solve this problem for a class of diffeomorphisms having a globally attracting fixed point. Furthermore we consider how the solution fields depend on the diffeomorphism. As an example we show that for certain parameters, the Hénon map is the time one map of a two dimensional flow.     

The logarithm on time scales

We briefly present the well-studied exponential function on a time scale and pose the problem of finding an appropriate logarithm function on a time scale.     

A tight lower bound for the completion time variance problem

We consider the completion time variance problem. Our main result is a tight lower bound for the mean completion time of an optimal sequence. This result can be applied to reduce the time required to solve the problem.     

Third-order right-focal multi-point problems on time scales

We are concerned with the existence and form of positive solutions to a third-order multi-point boundary-value problem on time scales with mixed derivatives. We find and utilize the Green function for the corresponding homogeneous right-focal problem as the kernel of an integral equation of Hammerstein-type. Two examples are included to illustrate the results.     

Unrelated parallel machine scheduling with past-sequence-dependent setup time and learning effects

In this article, we study an unrelated parallel machine scheduling problem with setup time and learning effects simultaneously. The setup time is proportional to the length of the already processed jobs. That is, the setup time of each job is past-sequence-dependent. The objective is to minimize the total completion time. We show that there exists a polynomial time solution for the proposed problem. We also discuss two special cases of the problem and show that they can be optimally solved by lower order algorithms.     

Parallel-machine scheduling with simple linear deterioration to minimize total completion time

We consider the parallel-machine scheduling problem in which the processing time of a job is a simple linear increasing function of its starting time. The objective is to minimize the total completion time. We give a fully polynomial-time approximation scheme (FPTAS) for the case with m identical machines, where m is fixed. This study solves an open problem that has been posed in the literature for ten years.     

A general method for finding the optimal threshold in discrete time

We develop an approach for solving one-sided optimal stopping problems in discrete time for general underlying Markov processes on the real line. The main idea is to transform the problem into an auxiliary problem for the ladder height variables. In case that the original problem has a one-sided solution and the auxiliary problem has a monotone structure, the corresponding myopic stopping time is optimal for the original problem as well. This elementary line of argument directly leads to a characterization of the optimal boundary in the original problem. The optimal threshold is given by the threshold of the myopic stopping time in the auxiliary problem. Supplying also a sufficient condition for our approach to work, we obtain solutions for many prominent examples in the literature, among others the problems of Novikov-Shiryaev, Shepp-Shiryaev, and the American put in option pricing under general conditions. As a further application we show that for underlying random walks (and Lévy processes in continuous time), general monotone and log-concave reward functions g lead to one-sided stopping problems.     

Sequential decision problems on isolated time domains

In this paper, we shall study the deterministic dynamic sequence problem on isolated time domains. After introducing the Euler equations and the transversality condition, we shall prove that the Euler equations and transversality condition are sufficient for the existence of the optimal solution. We shall also introduce the Bellman equation on isolated time scales. This equation will generalize the well-known Bellman equation in the theory of dynamic programming. As an application in financial economics, we shall optimize a sequence problem of growth model on isolated time domains.     

On-line scheduling of unit time jobs with rejection: minimizing the total completion time

We consider on-line scheduling of unit time jobs on a single machine with job-dependent penalties. The jobs arrive on-line (one by one) and can be either accepted and scheduled, or be rejected at the cost of a penalty. The objective is to minimize the total completion time of the accepted jobs plus the sum of the penalties of the rejected jobs.We give an on-line algorithm for this problem with competitive ratio . Moreover, we prove that there does not exist an on-line algorithm with competitive ratio better than 1.63784.     

The selection and scheduling of telecommunication calls with time windows

We consider the bandwidth scheduling problem that consists of selecting and scheduling calls from a list of available calls to be routed on a bandwidth-capacitated telecommunication network in order to maximize profit. Each accepted call should be routed within a permissible scheduling time window for a required duration. To author's knowledge, this study represents the first work on bandwidth scheduling with time windows. We present an integer programming formulation of the problem. We also propose a solution procedure based on the well-established Lagrangean relaxation technique. The results of extensive computational experiments over a wide range of problem structures indicate that the procedure is both efficient and effective.     

An optimal stocking problem to minimize the expected time to sellout

We consider an assortment planning problem where the objective is to minimize the expected time to sell all items in the assortment. We provide several structural results for the optimal assortment. We present a heuristic policy, which we prove is asymptotically optimal. We also show that there are alternate objective criteria under which the problem simplifies considerably.     

Input tracking for a parabolic equation on an infinite time interval

We study the input tracking problem for a parabolic equation on an infinite time interval on the basis of the measurement of phase coordinates. We suggest an algorithm stable under information noises and roundoff errors for the solution of the problem on the basis of constructions of dynamic inversion theory.     

Truck dock assignment problem with operational time constraint within crossdocks

In this paper, we consider a truck dock assignment problem with an operational time constraint in crossdocks where the number of trucks exceeds the number of docks available. The problem feasibility is affected by three factors: the arrival and departure time window of each truck, the operational time for cargo shipment among the docks, and the total capacity available to the crossdock. The objective is to find an optimal assignment of trucks that minimizes the operational cost of the cargo shipments and the total number of unfulfilled shipments at the same time. We combine the above two objectives into one term: the total cost, a sum of the total dock operational cost and the penalty cost for all the unfulfilled shipments. The problem is then formulated as an integer programming (IP) model. We find that as the problem size grows, the IP model size quickly expands to an extent that the ILOG CPLEX Solver can hardly manage. Therefore, two meta-heuristic approaches, Tabu Search (TS) and genetic algorithm (GA), are proposed. Computational experiments are conducted, showing that meta-heuristics, especially the Tabu search, dominate the CPLEX Solver in nearly all test cases adapted from industrial applications.     

Batch machine production with perishability time windows and limited batch size

This article provides a theoretical analysis of the problem of scheduling jobs in batches by family on a batch-processing machine, in the presence of perishability time windows of equal length. The problem arises in the context of production planning in a microbiological laboratory, and has application in wafer-fab production and for wireless broadcasting. The combined features of multiple families and time windows are new to the literature. The study is restricted to unit job processing times. We prove that the problem is NP-hard, thus solving an open problem by Uzsoy [24]. A Dynamic Programme is developed, with running time polynomial in the input variables of maximum batch size, the number of families and the length of the demand time horizon. In addition, we show that an heuristic approach to minimising the perishability time window can provide a 2-approximation to the optimum.     

Risk-sensitive control of continuous time Markov chains

We study risk-sensitive control of continuous time Markov chains taking values in discrete state space. We study both finite and infinite horizon problems. In the finite horizon problem we characterize the value function via Hamilton Jacobi Bellman equation and obtain an optimal Markov control. We do the same for infinite horizon discounted cost case. In the infinite horizon average cost case we establish the existence of an optimal stationary control under certain Lyapunov condition. We also develop a policy iteration algorithm for finding an optimal control.     

Lower bounds for blow-up time in parabolic problems under Dirichlet conditions

We consider an initial-boundary value problem for the semilinear heat equation whose solution may blow up in finite time. We use a differential inequality technique to determine a lower bound on blow-up time if blow-up occurs. A second method based on a comparison principle is also presented.     

Total completion time minimization in two-machine job shops with unit-time operations

We study the problem of minimizing total completion time in two-machine job shop with unit-time operations. We propose an efficient algorithm for the problem. The algorithm is polynomial with respect to a succinct encoding of the problem instances, where the number of bits necessary to encode a job with k operations is O(log(k + 1)). This result answers a long standing open question about the complexity of the problem.