Some Transportation Problems Under Uncertain Environments

2015 ◽  
pp. 225-365
Author(s):  
Pradip Kundu
Keyword(s):  
Uncertain Environments ◽  
Transportation Problems

scholarly journals PSK Method for Solving Mixed and Type-4 Intuitionistic Fuzzy Solid Transportation Problems

2019 ◽  
Vol 10 (2) ◽  
pp. 20-53 ◽  
Author(s):  
P. Senthil Kumar
Keyword(s):  
Fuzzy Number ◽  
Transportation Problem ◽  
Graphical Representation ◽  
Optimal Solution ◽  
Intuitionistic Fuzzy Number ◽  
Uncertain Environments ◽  
Transportation Problems ◽  
Intuitionistic Fuzzy ◽  
Triangular Intuitionistic Fuzzy Number ◽  
Fuzzy Optimal Solution

In this article, the author categorises the solid transportation problem (STP) under uncertain environments. He formulates the mixed and fully intuitionistic fuzzy solid transportation problems (FIFSTPs) and utilizes the triangular intuitionistic fuzzy number (TIFN) to deal with uncertainty and hesitation. The PSK (P. Senthil Kumar) method for finding an intuitionistic fuzzy optimal solution for fully intuitionistic fuzzy transportation problem (FIFTP) is extended to solve the mixed and type-4 IFSTP and the optimal objective value of mixed and type-4 IFSTP is obtained in terms of triangular intuitionistic fuzzy number (TIFN). The main advantage of this method is that the optimal solution of mixed and type-4 IFSTP is obtained without using the basic feasible solution and the method of testing optimality. Moreover, the proposed method is computationally very simple and easy to understand. Finally, the procedure for the proposed method is illustrated with the help of numerical examples which is followed by graphical representation of the finding.

Context-Driven Proactive Decision Support for Hybrid Teams

AI Magazine ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 41-57
Author(s):  
Manisha Mishra ◽  
Pujitha Mannaru ◽  
David Sidoti ◽  
Adam Bienkowski ◽  
Lingyi Zhang ◽  
...  
Keyword(s):  
Decision Support ◽  
Situational Awareness ◽  
Feature Space ◽  
Human Interaction ◽  
Superior Performance ◽  
Uncertain Environments ◽  
Cognitive States ◽  
Contextual Elements ◽  
Human Operators ◽  
Smart Machine

A synergy between AI and the Internet of Things (IoT) will significantly improve sense-making, situational awareness, proactivity, and collaboration. However, the key challenge is to identify the underlying context within which humans interact with smart machines. Knowledge of the context facilitates proactive allocation among members of a human–smart machine (agent) collective that balances auto­nomy with human interaction, without displacing humans from their supervisory role of ensuring that the system goals are achievable. In this article, we address four research questions as a means of advancing toward proactive autonomy: how to represent the interdependencies among the key elements of a hybrid team; how to rapidly identify and characterize critical contextual elements that require adaptation over time; how to allocate system tasks among machines and agents for superior performance; and how to enhance the performance of machine counterparts to provide intelligent and proactive courses of action while considering the cognitive states of human operators. The answers to these four questions help us to illustrate the integration of AI and IoT applied to the maritime domain, where we define context as an evolving multidimensional feature space for heterogeneous search, routing, and resource allocation in uncertain environments via proactive decision support systems.

Life-History Evolution in Uncertain Environments: Bet Hedging in Time

2006 ◽  
Vol 168 (3) ◽  
pp. 398
Author(s):  
Wilbur ◽  
Volker H. W. Rudolf
Keyword(s):  
Life History ◽  
Life History Evolution ◽  
Bet Hedging ◽  
Uncertain Environments ◽  
History Evolution

Travel by Design

2001 ◽  
Author(s):  
Marlon Boarnet ◽  
Randall C. Crane
Keyword(s):  
Urban Design ◽  
New Urbanism ◽  
Neighborhood Design ◽  
Transportation Problems ◽  
Systematic Assessment ◽  
The Right ◽  
Livable Communities

Can transportation problems be fixed by the right neighborhood design? The tremendous popularity of the "new urbanism" and "livable communities" initiatives suggests that many persons think so. As a systematic assessment of attempts to solve transportation problems through urban design, this book asks and answers three questions: Can such efforts work? Will they be put into practice? Are they a good idea?

scholarly journals Designing Multi-Agent System Organisations for Flexible Runtime Behaviour

2020 ◽  
Vol 10 (15) ◽  
pp. 5335
Author(s):  
Kathleen Keogh ◽  
Liz Sonenberg
Keyword(s):  
Design Method ◽  
Multi Agent System ◽  
Improve Performance ◽  
Uncertain Environments ◽  
Agent System ◽  
Meta Model ◽  
Design Time ◽  
Organisational Support ◽  
Multi Agent ◽  
Associated Design

We address the challenge of multi-agent system (MAS) design for organisations of agents acting in dynamic and uncertain environments where runtime flexibility is required to enable improvisation through sharing knowledge and adapting behaviour. We identify behavioural features that correspond to runtime improvisation by agents in a MAS organisation and from this analysis describe the OJAzzIC meta-model and an associated design method. We present results from simulation scenarios, varying both problem complexity and the level of organisational support provided in the design, to show that increasing design time guidance in the organisation specification can enable runtime flexibility afforded to agents and improve performance. Hence the results demonstrate the usefulness of the constructs captured in the OJAzzIC meta-model.

scholarly journals Least-looping stepping-stone-based ASM approach for transportation and triangular intuitionistic fuzzy transportation problems

2021 ◽  
Author(s):  
Kedar Nath Das ◽  
Rajeev Das ◽  
Debi Prasanna Acharjya
Keyword(s):  
Optimal Solution ◽  
Transportation Engineering ◽  
Key Factors ◽  
Solution Quality ◽  
Transportation Problems ◽  
Stepping Stone ◽  
Intuitionistic Fuzzy ◽  
Real World Problem ◽  
Statistical Results ◽  
Made In

AbstractTransportation problem (TP) is a popular branch of Linear Programming Problem in the field of Transportation engineering. Over the years, attempts have been made in finding improved approaches to solve the TPs. Recently, in Quddoos et al. (Int J Comput Sci Eng (IJCSE) 4(7): 1271–1274, 2012), an efficient approach, namely ASM, is proposed for solving crisp TPs. However, it is found that ASM fails to provide better optimal solution in some cases. Therefore, a new and efficient ASM appoach is proposed in this paper to enhance the inherent mechanism of the existing ASM method to solve both crisp TPs and Triangular Intuitionistic Fuzzy Transportation Problems (TIFTPs). A least-looping stepping-stone method has been employed as one of the key factors to improve the solution quality, which is an improved version of the existing stepping-stone method (Roy and Hossain in, Operation research Titus Publication, 2015). Unlike stepping stone method, least-looping stepping-stone method only deals with few selected non-basic cells under some prescribed conditions and hence minimizes the computational burden. Therefore, the framework of the proposed method (namely LS-ASM) is a combination of ASM (Quddoos et al. 2012) and least-looping stepping-stone approach. To validate the performance of LS-ASM, a set of six case studies and a real-world problem (those include both crisp TPs and TIFTPs) have been solved. The statistical results obtained by LS-ASM have been well compared with the existing popular modified distribution (MODI) method and the original ASM method, as well. The statistical results confirm the superiority of the LS-ASM over other compared algorithms with a less computationl effort.

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