A Faster Algorithm for the Limited-Capacity Many-to-Many Point Matching in One Dimension

Given two point sets S and T on a line, we present the first linear time algorithm for finding the limited capacity many-to-many matching (LCMM) between S and T improving the previous best known quadratic time algorithm. The aim of the LCMM is to match each point of S (T) to at least one point of T (S) such that the matching costs is minimized and the number of the points matched to each point is limited to a given number.Comment: 18 pages, 7 figures. arXiv admin note: text overlap with arXiv:1702.0108

A Fast and Efficient algorithm for Many-To-Many Matching of Points with Demands in One Dimension

Given two point sets S and T, a many-to-many matching with demands (MMD) problem is the problem of finding a minimum-cost many-to-many matching between S and T such that each point of S (respectively T) is matched to at least a given number of the points of T (respectively S). We propose the first O(n^2) time algorithm for computing a one dimensional MMD (OMMD) of minimum cost between S and T, where |S|+|T| = n. In an OMMD problem, the input point sets S and T lie on the real line and the cost of matching a point to another point equals the distance between the two points. We also study a generalized version of the MMD problem, the many-to-many matching with demands and capacities (MMDC) problem, that in which each point has a limited capacity in addition to a demand. We give the first O(n^2) time algorithm for the minimum-cost one dimensional MMDC (OMMDC) problem.Comment: 14 pages,8 figures. arXiv admin note: substantial text overlap with arXiv:1702.0108

The Relationship between Organizational Justice Perception and Job Satisfaction: a study on employees of Kerman University of Medical Sciences

Background: Motivated employees are the most valuable resource of the organization. Thus, considering their needs and satisfaction is important. Organizational justice, due to its significant impacts on the organizational and individual work outcomes, employees’ attitudes and behaviors like job satisfaction, is of a great importance. The aim of this study was to investigate the relationship between organizational justice perception and job satisfaction among employees of Kerman University of Medical Sciences. Methods: The target population of this study was headquartering employees of Kerman University of Medical Sciences, among whom 285 ones were selected. For the assessment of distributive justice Niehoff and Moorman questionnaire, for procedural and interactional justice Moorman questionnaire and for job satisfaction JSS (Job Satisfaction Survey) questionnaire were used. Results: All three dimensions of organizational justice including distributive, procedural and interactional justice had a significant relationship with job satisfaction. But among the three dimensions of organizational justice, only distributive and interactional justice could predict job satisfaction. Also, organizational justice and job satisfaction of employees were not significantly different based on sex, age group, job tenure, employment status, and education. Conclusion: Since organizational justice and its dimensions have a significant relationship with job satisfaction and organizational justice can predict job satisfaction, managers should pay attention to organizational justice which leads to enhanced job satisfaction. Keywords: Organizational justice, Distributive justice, Procedural justice, Interactional justice, Job satisfactio

Computing a many-to-many matching with demands and capacities between two sets using the Hungarian algorithm

Given two sets A={a_1,a_2,...,a_s} and {b_1,b_2,...,b_t}, a many-to-many matching with demands and capacities (MMDC) between A and B matches each element a_i in A to at least \alpha_i and at most \alpha'_i elements in B, and each element b_j in B to at least \beta_j and at most \beta'_j elements in A for all 1=<i<=s and 1=<j<=t. In this paper, we present an algorithm for finding a minimum-cost MMDC between A and B using the well-known Hungarian algorithm.Comment: 8 pages, 1 figur

Evaluating strategies for implementing industry 4.0: a hybrid expert oriented approach of B.W.M. and interval valued intuitionistic fuzzy T.O.D.I.M.

open access articleDeveloping and accepting industry 4.0 influences the industry structure and customer willingness. To a successful transition to industry 4.0, implementation strategies should be selected with a systematic and comprehensive view to responding to the changes flexibly. This research aims to identify and prioritise the strategies for implementing industry 4.0. For this purpose, at first, evaluation attributes of strategies and also strategies to put industry 4.0 in practice are recognised. Then, the attributes are weighted to the experts’ opinion by using the Best Worst Method (BWM). Subsequently, the strategies for implementing industry 4.0 in Fara-Sanat Company, as a case study, have been ranked based on the Interval Valued Intuitionistic Fuzzy (IVIF) of the TODIM method. The results indicated that the attributes of ‘Technology’, ‘Quality’, and ‘Operation’ have respectively the highest importance. Furthermore, the strategies for “new business models development’, ‘Improving information systems’ and ‘Human resource management’ received a higher rank. Eventually, some research and executive recommendations are provided. Having strategies for implementing industry 4.0 is a very important solution. Accordingly, multi-criteria decision-making (MCDM) methods are a useful tool for adopting and selecting appropriate strategies. In this research, a novel and hybrid combination of BWM-TODIM is presented under IVIF information