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Optimal sequencing in the presence of setup times for tow/barge traffic through a river lock

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TLDR
Dependence on the objective chosen, it is able to show that certain ordering protocols may be used to markedly reduce the sequencing search space for N tow/barges from the order of N ! to 2 N.
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This article is published in European Journal of Operational Research.The article was published on 2008-06-16. It has received 51 citations till now.

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Journal ArticleDOI

A survey of scheduling problems with setup times or costs

TL;DR: An extensive review of the scheduling literature on models with setup times (costs) from then to date covering more than 300 papers is provided, which classifies scheduling problems into those with batching and non-batching considerations, and with sequence-independent and sequence-dependent setup times.
Journal ArticleDOI

Integration of inland waterway transport in the intermodal supply chain: a taxonomy of research challenges

TL;DR: In this paper, the authors identify research opportunities which will enable the further integration of inland waterway transport in the intermodal supply chain and propose a system wide model for IWT, integration of operational planning systems and analysis of bundling networks.
Journal ArticleDOI

Simulation of alternative approaches to relieving congestion at locks in a river transportion system

TL;DR: A discrete-event simulation model to investigate the impact of alternative decision rules and infrastructural improvements to relieve traffic congestion in a section of the Upper Mississippi River navigation system reveals that some improvement in performance can be achieved by scheduling lock activity with priority given to vessels with shortest average processing and lock set-up times.
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The generalized lock scheduling problem: An exact approach

TL;DR: An integrated approach to solving the generalized lock scheduling problem using a mixed integer linear programming model and showing that small instances incorporating a wide range of real-life constraints can be solved to optimality.
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Exact and heuristic methods for placing ships in locks

TL;DR: A multi-order best fit heuristic for the ship placement problem is introduced, and its performance is compared with that of the left-right-left-back heuristic, and it clearly outperforms the exact approach with respect to calculation time.
References
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Journal ArticleDOI

A survey of scheduling problems with setup times or costs

TL;DR: An extensive review of the scheduling literature on models with setup times (costs) from then to date covering more than 300 papers is provided, which classifies scheduling problems into those with batching and non-batching considerations, and with sequence-independent and sequence-dependent setup times.
Journal ArticleDOI

A review of scheduling research involving setup considerations

TL;DR: A comprehensive review of the literature on scheduling problems involving setup times (costs) classifies scheduling problems into batch and non-batch, sequence-independent and sequence-dependent setup, and categorizes the literature according to the shop environments of single machine, parallel machines, flowshops, and job shops.
Journal ArticleDOI

Three Heuristic Rules for Sequencing Jobs to a Single Production Facility

TL;DR: The study consists of examining the performance of the three heuristic rules in terms of the optimal downtime obtained by the branch and bound algorithm and the downtime which results from a random sequencing of jobs through the facility.
Journal ArticleDOI

Sequence dependent set-up times and job sequencing

TL;DR: A procedure that classifies set-up operations and predicts the set- up times is developed and a method for sequencing the jobs so as to minimize the total set-ups time is developed.
Journal ArticleDOI

A Hybrid Genetic Algorithm for the Single Machine Scheduling Problem

TL;DR: A hybrid genetic algorithm (HGA) is proposed for the single machine, single stage, scheduling problem in a sequence dependent setup time environment within a fixed planning horizon (SSSDP), which incorporates the elitist ranking method, genetic operators, and a hill-climbing technique in each searching area.
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