Flexible strategic planning of transport systems

Juan, Carmen; Olmos, F.; Ashkeboussi, Rahim

doi:10.1080/03081060.2012.710032

Cited by 5 publications

(4 citation statements)

References 29 publications

(23 reference statements)

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“…This is true in the case when the cost of the ship's stay in port is relatively low and the situation on the shipping market is unfavourable so it is worth to keep the ship for an extended period in port, resulting in higher realized gain in longer period. In the case when the cost of the ship's stay in port is high or in the case when the freight rates are high, ship's operator may opt for a shorter service time in the port, which entails a greater number of service places and higher operating costs per hour (Hess, S., Hess, M. 2010;Juan et al 2012).…”

Section: Practical Example and Results Analysismentioning

confidence: 99%

Multi-Objective Ship’s Cargo Handling Model

Hess

2013

Transport

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This paper proposes a new optimization model for ship's cargo handling operations which solution gives the structure of cargo handling resources required, along with attaining the minimum total 'in-port' costs and the minimum of time required for completion of cargo operations. Due to complexity of the model which consists of composite multi-objective functions together with several decision variables and constraints, the solution has been sought by utilization of an adapted genetic algorithm combined with a hybrid algorithm. Testing of the model on real world data yielded acceptable results in a short time. In the course of decision making, the ship's operator can, on the basis of the proposed model and taking into consideration shipping market data, choose appropriate variation of the returned solution, which incorporates minimum costs, minimum of operational time and related cargo handling resources.

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Section: Practical Example and Results Analysismentioning

confidence: 99%

Multi-Objective Ship’s Cargo Handling Model

Hess

2013

Transport

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“…Not only for air carriers, but for any transport organization, dynamic strategy has been also proven as a beneficial practice (Juan, Olmos & Ashkeboussi, 2012). Decisions based on this technique are constantly revaluated as constraints evolve and the boundary conditions are modified, featuring a more flexible behavior against changes in the environment.…”

Section: Strategymentioning

confidence: 99%

Artificial Intelligence potential within airlines: a review on how AI can enhance strategic decision-making in times of COVID-19

Pérez-Campuzano

Ortega

Andrada

et al. 2021

J. airl. airpt. manag.

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Purpose: Airline strategy relies on the competitive environment analysis and the management of resources. Artificial Intelligence (AI) algorithms are being increasingly deployed throughout several industries. COVID-19 has further stressed a sector where firms have historically struggled to sustain profitability.The purpose is to explore the potential of AI applications regarding strategic decision-making in airlines in times of crisis and to depict a roadmap to encourage scholars and practitioners to jointly implement these tools within corporations.Design/methodology/approach: This study firstly reviews the state-of-the-art regarding transport organization trends with focus on airline strategy and finance as well as AI tools, supported by the collaboration of a former airline digitalization strategist. Secondly, the potential of the latter to be applied in those functions is analyzed, considering different Machine Learning (ML) methods and algorithms.Findings: Some applications or pathways are identified as of particular interest for the airlines’ strategic decision-making process. Most of them are based on ML algorithms and training methods that are currently underused or disregarded in certain business areas, such as Neural Network models for unsupervised market analysis or supervised cost estimation.Research limitations/implications: Focus is on airline strategy and finance, keeping engineering or operational applications out of the scope.Practical implications: Proposed guidance may promote the deployment of AI tools which currently lack practical implementation in certain business areas.Social implications: Showcased guidance may revert into a closer collaboration between business and academia.Originality/value: Comprehensive review of current airlines’ strategic levers and identification of promising AI pathways to be further explored.

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“…Joint Monte Carlo simulation of such processes leads to five-dimensional scenario spaces at each one of the agreed decision dates. Then, using the methodology described in Juan et al (2012, 2016), a tree structure is built so that each node in the tree contains a possible combination of outcomes for the processes mentioned before while scenarios at consecutive decision dates are connected by suitable transition probabilities.…”

Section: Risk Analysis Of the Optionsmentioning

confidence: 99%

“…Both frequency of the MoS maritime service (three departures a day in each direction) and average freight (€550 per container) are set to be competitive with the corresponding road alternative. Fleet composition will be chosen among five possible types of containerships, which provide a wide range of capacity, speed, terminal handling efficiency ratios and fuel consumption combinations (Juan et al , 2012).…”

Section: Case Studymentioning

confidence: 99%

Public–private equity joint ventures and risk transfers in motorways of the sea

Juan

Olmos

2019

BEPAM

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Purpose The purpose of this paper is to present a new scheme of public–private partnership (PPP) within the framework of motorways of the sea (MoS) similar to that of an equity joint venture along with a methodology for valuing risk transfers arising from options embedded in the clauses included in such agreement. Design/methodology/approach The architecture of the proposed PPP is an adaptation to the scope of a MoS of collaborative schemes commonly used in industry such as equity joint ventures. The methodology for valuing options involved making use of a valuation tree of optimal cashflows along with algorithm designs from the field of financial and real options. Findings The proposed structure of public–private equity joint venture (PPEJV) increases the stability of private–public collaboration as compared with standard PPPs, so as to achieve the desired modal shift. The analyzed case study shows how the methodology provides valuable numerical information for both negotiating partners and policy makers. Practical implications This study provides a quantitative tool for policy makers to redefine the role that public agents and public funds should play in a future sustainable mobility model. Originality/value The originality of the authors’ contribution to the field of PPPs in transport is triple. First, there is no precedent in the literature on PPPs of an architecture similar to that of the proposed PPEJV. Second, unlike the usual practice in the valuation of financial or real options, no prior structure is assumed for modelling the behaviour of cashflows. Third, the type of options addressed is not usual neither in the real options literature in general nor in the valuation of guarantee mechanisms included in PPPs in particular.

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Flexible strategic planning of transport systems

Cited by 5 publications

References 29 publications

Multi-Objective Ship’s Cargo Handling Model

Multi-Objective Ship’s Cargo Handling Model

Artificial Intelligence potential within airlines: a review on how AI can enhance strategic decision-making in times of COVID-19

Public–private equity joint ventures and risk transfers in motorways of the sea

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