In this paper, we consider that the judgments provided by the decision makers (DMs) cannot be aggregated and revised, then define them as hesitant judgments to describe the hesitancy experienced by the DMs in decision making. If there exist hesitant judgments in analytic hierarchy process-group...

In this paper, we conduct a study of the job-shop scheduling problem with reverse flows. This NP-hard problem is characterized by two flows of jobs that cover the same machines in opposite directions. The objective is to minimize the maximal completion time of the jobs (i.e., the makespan).

High logistics and handling costs prevent the bioenergy industry from making a greater contribution to the present energy market. Therefore, a mathematical model, OPTIMASS, is presented to optimise strategic (e.g. facility location and type) and tactical (e.g. allocation) decisions in all kinds...

Mathematical programming representation has been recently used to describe the behavior of discrete event systems as well as their formal properties. This new way of representing discrete event systems paves the way to the creation of simpler mathematical programming models that reduce the...

Seeking to reduce the potential impact of delays on radiation therapy cancer patients such as psychological distress, deterioration in quality of life and decreased cancer control and survival, and motivated by inefficiencies in the use of expensive resources, we undertook a study of scheduling...

Hierarchical organizations, especially in government agencies, are known by their pyramidal structures and continuous training needs resulting from promotions and/or assignments. Using scientific and rational methods in the job analysis/description, recruitment/selection, assignment, performance...

Support Vector Machines (SVMs) is known to be a powerful nonparametric classification technique even for high-dimensional data. Although predictive ability is important, obtaining an easy-to-interpret classifier is also crucial in many applications. Linear SVM provides a classifier based on a...

We study a class of mixed-integer programs for solving linear programs with joint probabilistic constraints from random right-hand side vectors with finite distributions. We present greedy and dual heuristic algorithms that construct and solve a sequence of linear programs. We provide optimality...

An important issue in the management of urban traffic networks is the estimation of origin–destination (O–D) matrices whose entries represent the travel demands of network users. We discuss the challenges of O–D matrix estimation with incomplete, imprecise data. We propose a fuzzy...

When modeling optimal product mix under emission restrictions produces a solution with unacceptable level of profit, analyst is moved to investigate the cause(s). Interior analysis (IA) is proposed for this purpose. With IA, analyst can investigate the impact of accommodating emission controls...