30,502 research outputs found
Dynamic transport scheduling under multiple resource constraints
This paper presents a heuristic for the dynamic vehicle scheduling problem with multiple resource capacity constraints. In the envisaged application, an automated transport system using Automated Guided Vehicles, bottleneck resources are (1) vehicles, (2) docks for loading/unloading, (3) vehicle parking places, and (4) load storage space. This problem is hard, because interrelated activities (loading, transportation, unloading) at several geographical locations have to be scheduled under multiple resource constraints, where the bottleneck resource varies over time. Besides, the method should be suitable for real-time planning. We developed a dedicated serial scheduling method and analyzed its dynamic behavior using discrete event simulation. We found that our method is very well able to find good vehicle schedules satisfying all resource constraints. For comparison, we used a simple approach where we left out the resource constraints and extended the processing times by statistically estimated waiting times to account for finite capacities. We found that our newly designed method finds better schedules in terms of service levels
Hybrid job shop scheduling
We consider the problem of scheduling jobs in a hybrid job shop. We use the term\ud
'hybrid' to indicate that we consider a lot of extensions of the classic job shop, such as transportation times, multiple resources, and setup times. The Shifting Bottleneck procedure can be generalized to deal with those extensions. We test this approach for an assembly shop. In this shop, we study the influence of static and dynamic scheduling, setup times, batch sizes, and the arrival process of the jobs
The lockmaster's problem.
Inland waterways form a natural network that is an existing, congestion free infrastructure with capacity for more traffic.Transportation of goods by ship is widely promoted as it is a reliable, efficient and environmental friendly way of transport. A bottleneck for transportation over water are the locks that manage the water level. The lockmaster's problem concerns the optimal strategy for operating such a lock. In the lockmaster's problem we are given a lock, a set of ships coming from downstream that want to go upstream, and another set of ships coming from upstream that want to go downstream. We are given the arrival times of the ships and a constant lockage time; the goal is to minimize total waiting time of the ships. In this paper a dynamic programming algorithm (DP) is proposed that solves the lockmaster's problem in polynomial time. We extend this DP to different generalizations that consider weights, water usage, capacity, and (a fixed number of) multiple chambers. Finally, we prove that the problem becomes strongly NP-hard when the number of chambers is part of the input.Lock scheduling; Batch scheduling; Dynamic programming; Complexity;
On the global stability of departure time user equilibrium: A Lyapunov approach
In (Jin, 2018), a new day-to-day dynamical system was proposed for drivers'
departure time choice at a single bottleneck. Based on three behavioral
principles, the nonlocal departure and arrival times choice problems were
converted to the local scheduling payoff choice problem, whose day-to-day
dynamics are described by the Lighthill-Whitham-Richards (LWR) model on an
imaginary road of increasing scheduling payoff. Thus the departure time user
equilibrium (DTUE), the arrival time user equilibrium (ATUE), and the
scheduling payoff user equilibrium (SPUE) are uniquely determined by the
stationary state of the LWR model, which was shown to be locally,
asymptotically stable with analysis of the discrete approximation of the LWR
model and through a numerical example. In this study attempt to analytically
prove the global stability of the SPUE, ATUE, and DTUE. We first generalize the
conceptual models for arrival time and scheduling payoff choices developed in
(Jin, 2018) for a single bottleneck with a generalized scheduling cost
function, which includes the cost of the free-flow travel time. Then we present
the LWR model for the day-to-day dynamics for the scheduling payoff choice as
well as the SPUE. We further formulate a new optimization problem for the SPUE
and demonstrate its equivalent to the optimization problem for the ATUE in
(Iryo and Yoshii, 2007). Finally we show that the objective functions in the
two optimization formulations are equal and can be used as the potential
function for the LWR model and prove that the stationary state of the LWR
model, and therefore, the SPUE, DTUE, and ATUE, are globally, asymptotically
stable, by using Lyapunov's second method. Such a globally stable behavioral
model can provide more efficient departure time and route choice guidance for
human drivers and connected and autonomous vehicles in more complicated
networks.Comment: 17 pages, 3 figure
Control of a lane-drop bottleneck through variable speed limits
In this study, we formulate the VSL control problem for the traffic system in
a zone upstream to a lane-drop bottleneck based on two traffic flow models: the
Lighthill-Whitham-Richards (LWR) model, which is an infinite-dimensional
partial differential equation, and the link queue model, which is a
finite-dimensional ordinary differential equation. In both models, the
discharging flow-rate is determined by a recently developed model of capacity
drop, and the upstream in-flux is regulated by the speed limit in the VSL zone.
Since the link queue model approximates the LWR model and is much simpler, we
first analyze the control problem and develop effective VSL strategies based on
the former. First for an open-loop control system with a constant speed limit,
we prove that a constant speed limit can introduce an uncongested equilibrium
state, in addition to a congested one with capacity drop, but the congested
equilibrium state is always exponentially stable. Then we apply a feedback
proportional-integral (PI) controller to form a closed-loop control system, in
which the congested equilibrium state and, therefore, capacity drop can be
removed by the I-controller. Both analytical and numerical results show that,
with appropriately chosen controller parameters, the closed-loop control system
is stable, effect, and robust. Finally, we show that the VSL strategies based
on I- and PI-controllers are also stable, effective, and robust for the LWR
model. Since the properties of the control system are transferable between the
two models, we establish a dual approach for studying the control problems of
nonlinear traffic flow systems. We also confirm that the VSL strategy is
effective only if capacity drop occurs. The obtained method and insights can be
useful for future studies on other traffic control methods and implementations
of VSL strategies.Comment: 31 pages, 14 figure
Freeway lane-changing: some empirical findings
Lane changing activity is thought to play an important role in the capacity degradation of congested freeways. However, proofs of this negative impact are scarce due to the difficulties in obtaining suitable data. In this paper, the lane changing activity in the B-23 freeway accessing the city of Barcelona is analyzed. Lane changes (LC) were video recorded in six different stretches from where loop detector measurements were also available. The obtained database allowed finding a consistent relationship between LC activity and congestion. LC peaks in all analyzed sections when they become congested. This is particularly intense at the traffic breakdown, between congested and free flowing conditions. As an example, it is observed that LC activity peaks just downstream of a fixed bottleneck where free-flowing conditions are recovered. In addition, data show that the larger the lane changing rates, the smaller the maximum observable flows, supporting the hypothesis that LC is a key contributor to a capacity drop. In spite of all these findings, this research highlights the difficulty in obtaining a suitable database to definitively answer most of the research questions regarding freeway lane-changing. The spatial coverage of measurements is one of the major drawbacks. To this end, a careful planning of the data collection is necessary in order to obtain meaningful conclusions.Postprint (published version
Speeding up Martins' algorithm for multiple objective shortest path problems
The latest transportation systems require the best routes in a large network with respect to multiple objectives simultaneously to be calculated in a very short time. The label setting algorithm of Martins efficiently finds this set of Pareto optimal paths, but sometimes tends to be slow, especially for large networks such as transportation networks. In this article we investigate a number of speedup measures, resulting in new algorithms. It is shown that the calculation time to find the Pareto optimal set can be reduced considerably. Moreover, it is mathematically proven that these algorithms still produce the Pareto optimal set of paths
A hybrid shifting bottleneck-tabu search heuristic for the job shop total weighted tardiness problem
In this paper, we study the job shop scheduling problem with the objective of minimizing the total weighted tardiness. We propose a hybrid shifting bottleneck - tabu search (SB-TS) algorithm by replacing the reoptimization step in the shifting bottleneck (SB) algorithm by a tabu search (TS). In terms of the shifting bottleneck heuristic, the proposed tabu search optimizes the total weighted tardiness for partial schedules in which some machines are currently assumed to have infinite capacity. In the context of tabu search, the shifting bottleneck heuristic features a long-term memory which helps to diversify the local search. We exploit this synergy to develop a state-of-the-art algorithm for the job shop total weighted tardiness problem (JS-TWT). The computational
effectiveness of the algorithm is demonstrated on standard benchmark instances from the literature
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