Decision making plays an important role in economic, management, business, marketing, psychology, philosophy, mathematics, statistics, and many other fields. In each field, decision making consists of identifying the values, uncertainties, and other issues that define the decision. Randomness and fuzziness or vagueness are two major sources of uncertainty in the real world. Practical applications in areas of industrial engineering, management, and economics, are such that decision-makers are being confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and a decision making has to be performed under such a twofold uncertain environment of co-occurrence of randomness and fuzziness. This paper pre...
Recent advances in decision making have incorporated both risk and ambiguity in decision theory and ...
[[abstract]]In real-world transportation planning decision (TPD) problems, input data or related par...
There exist techniques for decision making under specific types of uncertainty, such as probabilisti...
In the context of logistics and transportation, this paper discusses how simheuristics can be extend...
Covering in detail both theoretical and practical perspectives, this book is a self-contained and sy...
The objective of this investigation is to formulate a fixed charge (FC) solid transportation problem...
In this paper, a fuzzy-stochastic optimization model is developed for an intermodal fleet management...
This paper develops a stochastic fuzzy decision making method to solve a class of decision making pr...
AbstractIn this paper, the vehicle routing problem with fuzzy demands (VRPFD) is considered, and a f...
Decision making under uncertainty requires not only measures of the uncertainty of situations that w...
Decision has inspired reflection of many thinkers since the ancient times. With the rapid developmen...
Combined cargo transportation in Ukraine is characterized by the presence of uncertain risks. The ai...
Managers often deal with uncertainty of a different nature in their decision processes. They can enc...
peer reviewedThere are many examples of problems in transportation where some elements are uncertain...
Stochasticity and ambiguity are two aspects of uncertainty in economic problems. In the case of inve...
Recent advances in decision making have incorporated both risk and ambiguity in decision theory and ...
[[abstract]]In real-world transportation planning decision (TPD) problems, input data or related par...
There exist techniques for decision making under specific types of uncertainty, such as probabilisti...
In the context of logistics and transportation, this paper discusses how simheuristics can be extend...
Covering in detail both theoretical and practical perspectives, this book is a self-contained and sy...
The objective of this investigation is to formulate a fixed charge (FC) solid transportation problem...
In this paper, a fuzzy-stochastic optimization model is developed for an intermodal fleet management...
This paper develops a stochastic fuzzy decision making method to solve a class of decision making pr...
AbstractIn this paper, the vehicle routing problem with fuzzy demands (VRPFD) is considered, and a f...
Decision making under uncertainty requires not only measures of the uncertainty of situations that w...
Decision has inspired reflection of many thinkers since the ancient times. With the rapid developmen...
Combined cargo transportation in Ukraine is characterized by the presence of uncertain risks. The ai...
Managers often deal with uncertainty of a different nature in their decision processes. They can enc...
peer reviewedThere are many examples of problems in transportation where some elements are uncertain...
Stochasticity and ambiguity are two aspects of uncertainty in economic problems. In the case of inve...
Recent advances in decision making have incorporated both risk and ambiguity in decision theory and ...
[[abstract]]In real-world transportation planning decision (TPD) problems, input data or related par...
There exist techniques for decision making under specific types of uncertainty, such as probabilisti...