A review and analysis of “graph theoretical-matrix permanent” approach to decision making with example applications

Baykasoğlu, Adil

doi:10.1007/s10462-012-9354-y

Cited by 51 publications

(41 citation statements)

References 73 publications

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“…If node i is more important than node j, a directed edge is drawn from i to j (e.g., e ij ) and vice versa [49]. To better understand this approach, the graph along with criteria, sub criteria, and interaction between them, based on a graph theoretical-matrix permanent-decision making approach, is depicted in Figure 3 (criteria are represented with C i ) [50].…”

Section: Anfis and Fuzzy C-means Clusteringmentioning

confidence: 99%

“…Step 2: [50]. At bene cial criteria, the lower and upper limit of the alternative C i assigned 0 and 1, respectively, and for the other in the inter-values de nition in Eq.…”

Section: Anfis and Fuzzy C-means Clusteringmentioning

confidence: 99%

“…(5). The values must be sorted in descending order and the highest value is the best alternative (the most reliable route) [50]: In the following, the steps of applying GT-MP-DM to a relief routing problem to prioritize a ected points of clusters 1 and 2 are described. It is worth mentioning that prioritization criteria for the a ected points of cluster 1 are related to the route reliability, and prioritization of a ected points of cluster 2 is based on the other criteria that a ect the acceleration of relief distribution operations, as mentioned before.…”

Section: Anfis and Fuzzy C-means Clusteringmentioning

confidence: 99%

“…In all problems, there is one depot for air vehicles. Also, the values of the capacity parameter come from a uniform distribution, U (50,60), and the values of transportation time are selected from a uniform distribution, U (10,60).…”

Section: Evaluation Of the E Ciency Of Meta-heuristic Algorithmsmentioning

confidence: 99%

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A cluster-based emergency vehicle routing problem in disaster with reliability

et al. 2017

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Abstract. In the event of natural disasters, relief distribution is the most challenging problem in emergency transportation. What is important in response to disaster is victims' relief in disaster areas with the quick distribution of vital commodity. In this regard, damage to infrastructure (e.g., roads) can make trouble in designing a distribution network. Therefore, this paper considers a problem using a three-stage approach. In the rst stage, pre-processing of model inputs is done through an Arti cial Neural Fuzzy Inference System (ANFIS) followed by investigating the safest route for each cluster using decision-making techniques and graph theory. In the second stage, a heterogeneous multi-depot multimode vehicle routing problem is formulated for minimizing the transportation time and maximizing the reliability. Finally, since the routing problem is NP-hard, 2 multi-objective meta-heuristic algorithms, namely, Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Fire y Algorithm (MOFA), are proposed to obtain the optimal solution and their performances are compared through a set of randomly generated test problems. The results show that for this routing problem, the MOFF gives better solutions than NSGA-II does, and it performs well in terms of accuracy and solution time.

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Section: Anfis and Fuzzy C-means Clusteringmentioning

confidence: 99%

“…Step 2: [50]. At bene cial criteria, the lower and upper limit of the alternative C i assigned 0 and 1, respectively, and for the other in the inter-values de nition in Eq.…”

Section: Anfis and Fuzzy C-means Clusteringmentioning

confidence: 99%

Section: Anfis and Fuzzy C-means Clusteringmentioning

confidence: 99%

Section: Evaluation Of the E Ciency Of Meta-heuristic Algorithmsmentioning

confidence: 99%

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A cluster-based emergency vehicle routing problem in disaster with reliability

et al. 2017

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“…Many different state of the art methods were proposed in the literature to handle and solve MADM problems like AHP, ANP, TOPSIS, PROMETHEE, VIKOR, ELECTRE, GRA, LINMAP, conjoint analysis, multi-attribute utility theory, etc. (Baykasoglu, 2013).…”

Section: Fuzzy Graph Theoretical-matrix Permanent Approachmentioning

confidence: 99%

Route prioritisation in a multi-agent transportation environment via multi-attribute decision making

Baykasoğlu

Kaplanoğlu

Şahin

2016

IJDATS

Self Cite

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Effective management of the vehicles plays an important role in transportation sector. There are some novel approaches in software engineering which can be used to dynamically control the trucks. One of the example technologies is multi-agent systems. Multi-agent-based technologies could be used for truck dispatching in real time. The trucks in such systems have their own transportation plan and they can decide about their routes throughout their operations. Any truck agent must select a route to pickup or deliver a transportation order while doing its transportation operation. However, truck driver route preference is also crucial for the transportation performances because of morale, motivation and psychological conditions of drivers have a considerable effect on transportation operation success. In this paper, driver route preference model is incorporated into a multi-agent-based vehicle dispatching system which uses fuzzy graph theoretical-matrix permanent approach which is a novel method in multi-attribute decision making (MADM). The model is also compared with fuzzy TOPSIS method. Spearman rank correlation test is used to assess the correlation between the ranks.

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Managing the retail operations in the COVID‐19 pandemic: Evidence from Morocco

et al. 2022

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Novel coronavirus disease (COVID‐19) and resulting lockdowns have contributed to major retail operational disturbances around the globe, forcing retail organizations to manage their operations effectively. The impact can be measured as a black swan event (BSE). Therefore, to understand its impact on retail operations and enhance operational performance, the study attempts to evaluate retail operations and develop a decision‐making model for disruptive events in Morocco. The study develops a three‐phase evaluation approach. The approach involves fuzzy logic ( to measure the current performance of retail operations ), graph theory ( to develop an exit strategy for retail operations based on different scenarios ), and ANN and random forest‐based prediction model with K‐cross validation ( to predict customer retention for retail operations ). This methodology is preferred to develop a unique decision‐making model for BSE. From the analysis, the current retail performance index has been computed as “Average” level and the graph‐theoretic approach highlighted the critical attributes of retail operations. Further, the study identified triggering attributes for customer retention using machine learning‐based prediction models (MLBPM) and develops a contactless payment system for customers' safety and hygiene. The framework can be used on a periodic basis to help retail managers to improve their operational performance level for disruptive events.

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A review and analysis of “graph theoretical-matrix permanent” approach to decision making with example applications

Cited by 51 publications

References 73 publications

A cluster-based emergency vehicle routing problem in disaster with reliability

A cluster-based emergency vehicle routing problem in disaster with reliability

Route prioritisation in a multi-agent transportation environment via multi-attribute decision making

Managing the retail operations in the COVID‐19 pandemic: Evidence from Morocco

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