Intelligent Agents and Risk Based Model for Supply Chain Management

Smeureanu, Ion; Ruxanda, Gheorghe; Diosteanu, Andreea; Delcea, Camelia; Cotfas, Liviu‐Adrian

doi:10.3846/20294913.2012.702696

Cited by 14 publications

(8 citation statements)

References 10 publications

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“…High importance of project selection in the project life cycle while solving bid/no-bid problems, especially in the construction industry, have been analysed by Abbasianjahromi and Rajaie (2012). Risk can be analysed with the help of the following methods: based on fuzzy TOPSIS bid/no-bid model (Ravanshadnia, Rajaie 2013); in fuzzy environment, applying TOPSIS-F method (Tamošaitienė et al 2013); based on intelligent agents (Smeureanu et al 2012); RAMCAP (Risk Analysis and Management for Critical Asset Protection) by introducing new parameters that affect risk value (Yazdani et al 2011);and Fuzzy Synthetic Model (Abdul-Rahman et al 2013). In terms of risk management, it is important to consider the following issues:…”

Section: Review Of Risk In Construction Industrymentioning

confidence: 99%

Risk Management in Construction Projects

Iqbal

Choudhry

Holschemacher

et al. 2015

Technological and Economic Development of Economy

163

117

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Risk management is an important field of construction industry and has gained more importance internationally due to the latest researches carried out on a large scale. However, this relatively new field requires more attention to bring some benefit. Construction projects are facing a number of risks which have negative effects on project objects such as time, cost and quality. This study is based on findings of a questionnaire-based survey on risk management in construction projects in Pakistan, reporting the significance of different type of risk, ultimate responsibility for them and the effectiveness of some most common risk management techniques practiced in the industry. Two types of risk management techniques were considered: preventive techniques which can be used before the start of a project to manage risks that are anticipated during the project execution; and remedial techniques that are used during the execution phase once a risk has already occurred. The study revealed that financial issues for projects, accidents on site and defective design are the most significant risks affecting most of construction projects. As further reported, the contractor is responsible for management of most risks occurring at sites during the implementation phase, such as issues related to subcontractors, labour, machinery, availability of materials and quality, while the client is responsible for the risks such as financial issues, issues related to design documents, changes in codes and regulations, and scope of work. Further reported results of the analysis demonstrate that the production of proper schedule by getting updated data of the project and guidance from previous similar projects are the most effective preventive risk management techniques while close supervision and coordination within projects are the most effective remedial risk management techniques. It may be concluded that the most significant risks must be managed with greater effort to reduce/eliminate their effects on the project. As the study concludes, preparation of a proper schedule and good coordination during the implementation stage are very important as they may help project managers to focus on critical areas for better management of projects in Pakistan.

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Section: Review Of Risk In Construction Industrymentioning

confidence: 99%

Risk Management in Construction Projects

Iqbal

Choudhry

Holschemacher

et al. 2015

Technological and Economic Development of Economy

163

117

View full text Add to dashboard Cite

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“…SCM involves, among others, selection of reliable business partners (Brauers et al, 2008;Zavadskas et al, 2010;Plebankiewicz 2012, Smeureanu et al, 2012Zolfani et al, 2012), which is usually a complex multicriteria problem (Zavadskas & Turskis, 2011;Liou & Tseng, 2012). The chains, once constructed, should be checked in terms of their overall performance (Pan, Lee & Chen, 2011).…”

Section: Materials Supply Management In Constructionmentioning

confidence: 99%

Decision Model for Selecting Supply Sources of Road Construction Aggregates

Jaśkowski

Sobotka²,

Czarnigowska

2014

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The authors' recent survey on Polish road contractors' aggregate procurement methods indicates that optimization techniques are rarely used in practicedespite the fact that the material is to be transported from large distances and its sources are inconveniently distributed throughout the country. In search for economy in this respect, the authors propose mixed binary linear programming models to facilitate the contractor's logistic decisions. The purpose of these models is to find delivery quantities from a number of supply locations (of limited capacity and with a limited transportation potential) to predefined destinations along the road in a way that minimizes logistic costs. The problem considered is an extension to the classic transshipment problem, and allows for change of delivery destination along the route with the progress of works, and for constraints resulting from the schedule of the works.

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“…(Zolfani et al, 2012) proposed a hybrid MCDM model encompassing AHP and COPRAS-G methods for selecting company supplier. In the other work in supply chain management domain (Smeureanu et al, 2012) presented Intelligent agents and risk based model for supply chain management.…”

Section: Literature Reviewmentioning

confidence: 99%

New Integrated Approach for Solving a Supplier Selection Problem in a Competitive Environment

Shahmardan

Zadeh

2014

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The main objective of this paper is a presentation of new integrated approach for solving a supplier selection problem by the use of a defined technique, which derives from LPP (linear physical programming), and execution of F-PROMETHEE (fuzzy preference ranking method for enrichment evaluation) method as a ranking algorithm. The objective of supplier selection problem is an identification of suppliers that have the highest capability of responding desirably to firm's needs. Suppliers are ranked from the best to worst total performance regarding to use of a common set of criteria and measures. Defined method intends to take two considerable actions: to employ typically available information and lessen the burden of choosing of weights for DM (decision maker). Owing to the paucity of information, measuring of the exact value of the attributed weights of criteria and input data seem to be impossible. Therefore, the use of fuzzy techniques is justifiable. According to brought weights, F-PROMETHEE method is implemented to rank the suppliers. In previous works, weights of criteria were achieved in relation to DM's comments and there was less attention given to the fact that suppliers work in a competitive environment, furthermore, situations of rivals have not been considered as an important factor, precisely. In addressed approach, the information of the enterprise, which is working with DM and its rivals' information in different criteria, is regarded as input data and weighting of these criteria and ranking of those suppliers are conducted through a suggested algorithm.

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Intelligent Agents and Risk Based Model for Supply Chain Management

Cited by 14 publications

References 10 publications

Risk Management in Construction Projects

Risk Management in Construction Projects

Decision Model for Selecting Supply Sources of Road Construction Aggregates

New Integrated Approach for Solving a Supplier Selection Problem in a Competitive Environment

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