Search

Neutrosophic set (NS) is generalization of Intuitionistic Fuzzy Set (IFS) and Fuzzy Set (FS) where Neutrosophic Set(NS) is the collection of Membership, Non-Membership, Indeterminacy Membership of the constituent element. This paper includes the modified circle breaking techinque which is used to evaluate the Shortest Path Problem in which edge weight are protrayed in Single Valued Linear Heptagonal Neutrosophic Number (SVLHNN) and an numerical illustration is given for the efficiency of the given algorithm. [ABSTRACT FROM AUTHOR]

This paper considers SUB_GOALs by using basic A* algorithm and Subgoal Graphs in a hybrid approach to execute optimal route. SUB_GOALs identified with pre-searching from basic A* at break points and Subgoal Graphs at corners of obstacles are added to SUB_TABLE to expedite the final searching in the hybrid approach. Map to work on is divided to subregions with decision-making process by using line-of-sight to avoid redundant searching. In the final searching layer, all feasible SUB_GOALs gained from decision-making process in the same subregion are connected to find final solutions of routes. Solutions achieved in the divided subregions are evaluated and combined to discover the final optimal route. The proposed hybrid approach is applied to three different scenarios in various dimensions of maps. In these three scenarios, the shortest route without hitting obstacles is calculated as 46.67, 57.76 and 124.7 units, respectively, and compared with other search algorithms. Simulation results of route planning are demonstrated to exhibit the effectiveness of the proposed hybrid approach. [ABSTRACT FROM AUTHOR]

This article studies logical reconfiguration of reconfigurable manufacturing systems (RMS) to minimise production lead times and buffer inventory level when the process variations and worker utilisation are considered. Since the RMS must be flexible for different job orders, the design of RMS requires diagnostic methodology and stream of variations (SoV) theory for rapid ramp-up in order to control the process variations that might occur as time goes on. The flexibility of the manufacturing systems is represented by logical elements of RMS in terms of changeable production batch size. The three phases solution is proposed by (1) utilising SoV modelling to find the allowable production lead times, (2) finding the optimum buffer stock level and production capacity at changeable production batch size and (3) finding worker routings at optimum worker utilisation. Monte carlo simulation is employed at Phase 1 to get the optimum production lead times, Phase 2 decision is formulated as a stochastic two-stages programming where buffer inventory level (first stage decison) has to be established prior to changeable production batching at future period and shortest path problems (SPP) algorithm is used to find an optimum worker routing at Phase 3. A serial inventory production (SIP) is used as an example to answer the following research questions: (1) What is the impact of SoV on both buffer inventory allocation and worker routings? (2) When is logical reconfiguration most beneficial in improving SIP profitability? (3) What is the impact of logical reconfiguration on both cost and lead time reduction? Three instances are used to investigate the effect of logical reconfiguration on the different structure of SIP systems. The results and analysis indicate that consideration of SoV is capable of increasing the profit, reducing operation lead times and maximising worker utilisation. Finally, management decision-making is discussed among other concluding remarks. [ABSTRACT FROM PUBLISHER]

A pythagorean fuzzy set is a generalized fuzzy structure that copes with imprecisions of real life accurately and with a larger domain. The aim of this manuscript is to develop the notion of graph for newly established concept of interval‐valued Pythagorean fuzzy set. We introduced the concept of interval‐valued Pythagorean fuzzy graph (IVPyFG) and discussed its related ideas with the help of examples. The significance of using interval‐valued fuzzy concepts over non‐interval‐valued fuzzy concepts are demonstrated numerically. Further, the advantages of using the new approach over the pre‐existing ideas are demonstrated with the help of numerical examples. The main goal of this article is to study three types of decision‐making problems using the framework of IVPyFGs. These three problems include the problem of selection of the best university in a network of universities, a supply chain management problem and the shortest path problem. The comparison of the new approach toward these problems with existing approaches is also established. [ABSTRACT FROM AUTHOR]

Copyright of Scientific Papers of Silesian University of Technology. Organization & Management / Zeszyty Naukowe Politechniki Slaskiej. Seria Organizacji i Zarzadzanie is the property of Silesian Technical University, Organisation & Management Faculty and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this work we address a game theoretic variant of the shortest path problem, in which two decision makers (players) move together along the edges of a graph from a given starting vertex to a given destination. The two players take turns in deciding in each vertex which edge to traverse next. The decider in each vertex also has to pay the cost of the chosen edge. We want to determine the path where each player minimizes its costs taking into account that also the other player acts in a selfish and rational way. Such a solution is a subgame perfect equilibrium and can be determined by backward induction in the game tree of the associated finite game in extensive form. We show that the decision problem associated with such a path is PSPACE-complete even for bipartite graphs both for the directed and the undirected version. The latter result is a surprising deviation from the complexity status of the closely related game Geography . On the other hand, we can give polynomial time algorithms for directed acyclic graphs and for cactus graphs even in the undirected case. The latter is based on a decomposition of the graph into components and their resolution by a number of fairly involved dynamic programming arrays. Finally, we give some arguments about closing the gap of the complexity status for graphs of bounded treewidth. [ABSTRACT FROM AUTHOR]

Abstract: A supply chain network design needs to consider the future probability of reconfiguration due to some problems of disaster or price changes. The objective of this article is to design a reconfigurable supply chain network by optimizing inventory allocation and transportation routing. A two-stage programming is composed according to Benders decomposition by allocating inventory in advance and anticipating the changes of transportation routings; thus the transportation routing is stochastic in nature. In addition, the fuzzy shortest path is developed to solve the problem complexity in terms of the multi-criteria of lead time and capacity with an efficient computational method. The results and analysis indicate that the proposed two-stage programming with fuzzy shortest path surpasses the performance of shortest path problem with time windows and capacity constraint (SPPTWCC) in terms of less computational time and CPU memory consumption. Finally, management decision-making is discussed among other concluding remarks. [Copyright &y& Elsevier]