Coal bank scheduling using a mathematical programming model

Coals are extracted from mines and upgraded on the surface for customers. The upgraded coals must be aged at least four weeks in a bank before being supplied to customers. Different sizes of banks are required for different lengths of time at different points in time. Bigger banks increase the floor space capacity and reduce handling costs. The proper location of banks reduces the total space requirement and bank movement after building. In this paper, we address the bank size and location problem and solve it by using a mathematical programming approach.     

A scheduling policy with maximal stability region for ring networks with spatial reuse

A slotted ring that allows simultaneous transmissions of messages by different users is considered. Such a ring network is commonly called ring withspatial reuse. It can achieve significantly higher throughput than standard token rings but it also raises the issue of fairness since some nodes may be prevented from accessing the ring for long time intervals. Policies that operate in cycles and guarantee that a certain number (quota) of packets will be transmitted by every node in every cycle have been considered before to deal with the fairness issue. In this paper we address the problem of designing a policy that results in a stable system whenever the end-to-end arrival rates are within the stability region of the ring with spatial reuse (the stability region of the ring is defined as the set of end-to-end arrival rates for which there is a policy that makes the ring stable). We provide such a policy, which does not require knowledge of end-to-end arrival rates. The policy is an adaptive version of the quota policies and can be implemented with the same distributed mechanism. We use the Lyapunov test function technique together with methods from the theory of regenerative processes to derive our main results.This research was primarily done while the author was visiting INRIA in Rocquencourt, France. The author wishes to thank INRIA (projects ALGO, MEVAL and REFLECS) for a generous support. Additional support was provided by NSF Grants NCR-9206315 and CCR-9201078 and INT-8912631, and by Grant AFOSR-90-0107, and in part by NATO Grant 0057/89.The research of this author was supported in part by NSF under Grants NCR-9211417 and NCR-9406415, and by the New York State Center for Advanced Technology in Telecommunications, Polytechnic University.     

Dual decomposition of a single-machine scheduling problem

We design a fast ascent direction algorithm for the Lagrangian dual problem of the single-machine scheduling problem of minimizing total weighted completion time subject to precedence constraints. We show that designing such an algorithm is relatively simple if a scheduling problem is formulated in terms of the job completion times rather than as an 0–1 linear program. Also, we show that upon termination of such an ascent direction algorithm we get a dual decomposition of the original problem, which can be exploited to develop approximative and enumerative approaches for it. Computational results exhibit that in our application the ascent direction leads to good Lagrangian lower and upper bounds.     

Heuristics Based on Partial Enumeration for the Unrelated Parallel Processor Scheduling Problem

The classical deterministic scheduling problem of minimizing the makespan on unrelated parallel processors is known to be NP-hard in the strong sense. Given the mixed integer linear model with binary decision variables, this paper presents heuristic algorithms based on partial enumeration. Basically, they consist in the construction of mixed integer subproblems, considering the integrality of some subset of variables, formulated using the information obtained from the solution of the linear relaxed problem. Computational experiments are reported for a collection of test problems, showing that some of the proposed algorithms achieve better solutions than other relevant approximation algorithms published up to now.     

A branch and bound algorithm for scheduling trains in a railway network

The paper studies a train scheduling problem faced by railway infrastructure managers during real-time traffic control. When train operations are perturbed, a new conflict-free timetable of feasible arrival and departure times needs to be re-computed, such that the deviation from the original one is minimized. The problem can be viewed as a huge job shop scheduling problem with no-store constraints. We make use of a careful estimation of time separation among trains, and model the scheduling problem with an alternative graph formulation. We develop a branch and bound algorithm which includes implication rules enabling to speed up the computation. An experimental study, based on a bottleneck area of the Dutch rail network, shows that a truncated version of the algorithm provides proven optimal or near optimal solutions within short time limits.     

一个具有两类工件的多目标排序的NP-困难性

文章考虑具有两个工件集的单机排序问题.第一个工件集J1以加权完工时间和为目标函数,第二个工件集J2以最大加权完工时间为目标函数.问题的目标是寻找一种排序,使得两个目标函数的加权和达到最小,并证明该问题是强NP-困难的.     

微粒群算法及其在热轧生产调度中的应用

针对整数规划问题的特点,提出了一种在整数空间中进行进化计算的PSO算法,使微粒群的进化限于整数空间。给出了热轧生产调度问题的最优轧制单元数学规划模型。并将该方法成功应用于最优轧制单元求解。     

Little-Preemptive Scheduling on Unrelated Processors

We consider the preemptive scheduling of n independent jobs on m unrelated machines to minimize the makespan. Preemptive schedules with at most 2m–3 preemptions are built, which are optimal when the maximal job processing time is no more than the optimal schedule makespan. We further restrict the maximal job processing time and obtain optimal schedules with at most m–1 preemptions. This is better than the earlier known best bound of 4m ²–5m+2 on the total number of preemptions. Without the restriction on the maximal job processing time, our (2m–3)-preemptive schedules have a makespan which is no more than either of the following two magnitudes: (a) the maximum between the longest job processing time and the optimal preemptive makespan, and (b) the optimal nonpreemptive makespan. Our (m–1)-preemptive schedules might be at most twice worse than an optimal one.     

Control and scheduling in a two-station queueing network: Optimal policies and heuristics

Consider a two-station queueing network with two types of jobs: type 1 jobs visit station 1 only, while type 2 jobs visit both stations in sequence. Each station has a single server. Arrival and service processes are modeled as counting processes with controllable stochastic intensities. The problem is to control the arrival and service processes, and in particular to schedule the server in station 1 among the two job types, in order to minimize a discounted cost function over an infinite time horizon. Using a stochastic intensity control approach, we establish the optimality of a specific stationary policy, and show that its value function satisfies certain properties, which lead to a switching-curve structure. We further classify the problem into six parametric cases. Based on the structural properties of the stationary policy, we establish the optimality of some simple priority rules for three of the six cases, and develop heuristic policies for the other three cases.     

Algorithm for Scheduling Variable-Length Messages in WDM Networks

In this paper, we develop and analyze a simple algorithm for scheduling variable length messages in WDM networks with a passive star coupler. We base our schemes on a star topology with centralized control and use a scheduling algorithm similar to the process management in UNIX system. Every node and message have a scheduling priority associated with them. By comparing our algorithm with random select algorithm, we find that significant improvement in performance can be achieved with very little extra cost.