Bus Transport Process Networks with Arbitrary Launching Times

Ercsey, Zsolt; Nagy, Albert; Tick, József; Kovács, Zoltán

doi:10.12700/aph.18.4.2021.4.7

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…Process synthesis aims to find the optimal sub-structure and configuration of an extensive system of functional units and materials [13]. The method is applied in many fields, such as supply chain optimization [12], energy optimization [1], and vehicle scheduling [3,6]. The search for the optimal sub-network can be formulated as a MILP problem, where the number of binary variables equals the number of units, meaning the complexity of the problem is NP-hard.…”

Section: Introductionmentioning

confidence: 99%

Testing the selection heuristic of the Accelerated Branch and Bound method

Heinc,

Bánhelyi

2024

AMI

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This article examined the issue of selection heuristics for the ABB algorithm, a branch-and-bound method for determining the optimal solution structure in P-graphs. Previous studies have not investigated the possible effects of different heuristics on the running time of the ABB algorithm. In this study, we represent the results of applying three basic heuristics in randomly generated P-graphs. In particular, for P-graphs with matrix patterns, the LIFO heuristic is recommended because it performed the best, while the FIFO heuristic had the slowest running time.

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Section: Introductionmentioning

confidence: 99%

Testing the selection heuristic of the Accelerated Branch and Bound method

Heinc,

Bánhelyi

2024

AMI

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Literature Review on Research and Applications

Friedler

Orosz

Losada

2022

P-Graphs for Process Systems Engineering

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MILP models of a patient transportation problem

Tóth,

Hajba,

Horváth

2024

Cent Eur J Oper Res

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With ageing societies and increasing number of patients, there is a growing need for quality services that help transporting non-urgent patients to hospitals. In logistics, patient transportation problems are usually modeled as a dial-a-ride problem. In a Dial-a-Ride problem, a fleet of vehicles is providing the delivery services between the loading points and the delivery destinations. The demands are known in advance. In most cases the total travel distance of the vehicles is to be minimized. In this paper, we consider a specific dial-a-ride problem, where a single vehicle is used to transport patients to the same hospital. In determining the optimal route, the multiple and different travel needs of patients, such as their maximum travel time, are also taken into consideration. We introduce 4 different mixed integer linear programming models of the routing problem. Finally, the efficiency of the four models was compared using some real-life problems by solving them with a commercial solver.

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Bus Transport Process Networks with Arbitrary Launching Times

Cited by 4 publications

References 17 publications

Testing the selection heuristic of the Accelerated Branch and Bound method

Testing the selection heuristic of the Accelerated Branch and Bound method

Literature Review on Research and Applications

MILP models of a patient transportation problem

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