Mathematical programming models for supply chain production and transport planning

Mula, Josefa; Peidro, David; Díaz‐Madroñero, Manuel; Vicens, Eduardo Segarra

doi:10.1016/j.ejor.2009.09.008

Cited by 335 publications

(154 citation statements)

References 51 publications

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“…The vast majority of the literature reviewed [1,2,3,4], have formulated SC models as linear programming (LP), integer programming (IP) and mixed integer linear programming (MILP) problems. Declarative environments such as CLP facilitate problem modeling and introduction of logical and symbolic constraints [5,6].…”

Section: Problem Statement and Methodologymentioning

confidence: 99%

A declarative decision support framework for supply chain problems

Sitek

2016

Annals of Computer Science and Information Systems

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Abstract-The author presents a novel declarative approach to modeling, solving and decision support for supply chain problems as a declarative decision support framework. The proposed framework makes it possible to ask different types of questions (general, specific, logical etc.). The implementation of the framework was performed in the CLP (Constraint Logic Programming) environment.To increase the efficiency of the framework, particularly in the area of optimization made its integration with MP (Mathematical Programming) environment. The paper also presents the implementation of illustrative model, using the proposed framework. In addition, an efficiency analysis of the presented solution in relation to the application of mathematical programming have been conducted.

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Section: Problem Statement and Methodologymentioning

confidence: 99%

A declarative decision support framework for supply chain problems

Sitek

2016

Annals of Computer Science and Information Systems

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“…(18) and Eq. (19), where invs INVASION and conn CONN . In the previous section, the affinity between invader and connection is not defined explicitly.…”

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

“…These type affinities are transferred to construct the relationship between invader and connection. (19) i n n c Aff Aff TOLERATE (20) The entity and channel tolerance define the entrance of response. However, how does the response be performed?…”

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

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A multi-affinity model for logistics network inspired by bio-system

Hu¹,

Sheng²

2014

IJCIS

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How can we deal with the increasing scale of large logistics network for the booming economy? The structure, mechanisms and principles upon the logistics network show an evolutionary tendency which is complex, and interesting for designing and optimizing logistics network. The adaptability, stability and evolution capability are attractive for artificial intelligent systems. Inspired by biological systems, the metaphors for the structure and eight primary mechanisms are extracted to design a multi-affinity model for bio-inspired logistics network. Then, by mapping the biological elements and functions to logistics network, the evolutionary structure and simulation approach for logistics network are proposed and investigated by experiments. It is a novel way to study the complexity of logistics network and it is an interesting bionic approach for artificial network model. The research result can be employed to study the emergency features and collective behavior of large-scale logistics network.

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“…Secondly, traditional forecasting-based modelling does not representor only represents in a highly simplified waythe future actions of organisations such as government authorities (Timms, 2008) or transport suppliers (Mula et al, 2010) in response to future conditions, both within the transport sector and outside. Thirdly, exogenous factors from outside the transport sector but which impact on transport, such as economic growth or population growth, are typically treated in a highly simplified manner within the transport forecasting model, i.e.…”

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confidence: 99%

Imagineering Mobility: Constructing Utopias for Future Urban Transport

2014

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Over the past 50 years a growing body of work has sought to address the problem of planning for transportation in the long term future through scenario-building. Such thinking has generally been restricted to issues concerned with environmental sustainability and the 'images' of future transport so created are usually weak in terms of their social sustainability content, either treating social issues superficially, or ignoring them entirely, or even creating images that are socially undesirable. At the same time, there has generally been a marked decrease over the past 20 years in socially-oriented utopian thinking. As a direct result of these two factors, hardly any consideration has been given recently to imagining socially sustainable views of transport in a future utopia. The key underlying aim of this paper is to provide some background thinking about how this lack might be addressed. To do so, it examines concepts about utopia in terms of their form, content and function, and considers possible reasons for the recent decline in utopian thinking and their 'replacement' by a type of futures-thinking that is referred to as dystopian avoidance. It then examines transport characteristics of utopian thinking in urban planning in the 20 th Century and considers various 'antinomies of transport' with respect to future utopias. Based upon the insights gained, the paper comments on two existing 'practical' sets of transport-related scenarios in terms of their utopian and dystopian characteristics. One particular result is that the utopian aspects of these scenario sets in terms of their social content are relatively weak, in line with the hypothesised recent general decline in (social) utopian thinking. Various conclusions are made which emphasise the usefulness of utopian thinking in transport planning, particularly in participatory approaches. It is suggested that three elements of the transport system should be separately 'utopianised': the mobility of people and goods; physical aspects that facilitate or inhibit such mobility; and the system of governance with respect to formulating and implementing transport policy.

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Mathematical programming models for supply chain production and transport planning

Cited by 335 publications

References 51 publications

A declarative decision support framework for supply chain problems

A declarative decision support framework for supply chain problems

A multi-affinity model for logistics network inspired by bio-system

Imagineering Mobility: Constructing Utopias for Future Urban Transport

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