This study identifies the optimal route for transporting agricultural fruits using the Simple Additive Weighting (SAW) method within a Multicriteria Decision-Making (MCDM) framework. Data was gathered through a literature review on transportation principles, route selection criteria, and truck routes, identifying eight critical factors for route selection. Transportation route data were also systematically collected, forming the basis of the proposed conceptual framework. The SAW analysis identified the highest-scoring routes for each segment: Route A1 (6.35406), Route B1 (6.38532), Route C1 (6.26248), and Route D3 (5.29061). Historical data from the past five years confirmed consistency in route selection. Comparatively, Dijkstra's Algorithm, based on single factors like distance, time, or cost, proved less effective for agricultural transportation. In contrast, the SAW method, integrating multiple factors, ensured more accurate route selection. Key influencing factors included road conditions, infrastructure or road width, and facility availability. The optimal route from Thailand to China was Route A1-B1, passing through Chanthaburi, Rayong, Chonburi, Chachoengsao, Samut Prakan, Bangkok, Pathum Thani, Ayutthaya, Ang Thong, Sing Buri, Chai Nat, Nakhon Sawan, Phichit, Phitsanulok, Uttaradit, Phrae, Lampang, Phayao, and Chiang Rai, terminating at Chiang Khong Customs Checkpoint. These findings offer practical guidance for planning and decision-making in agricultural transportation routes.

In this paper, an alternative version of the fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations) method is proposed. Differently from other studies, preference functions used in PROMETHEE method are handled in terms of fuzzy distances between alternatives with respect to each criterion. In order to indicate the applicability of this method, the method is applied for a supplier selection problem in the literature. Ranking results are similar obtained by TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and fuzzy ELECTRE (ELimination Et Choix Traduisant la REalité) methods. The implementation of the proposed method indicates that the amount of computations is decreased and decision makers can easily reach to desirable solution.

It is necessary for companies and industries to select the most appropriate maintenance strategy to increase the reliability and safety level with reasonable cost. The primary objective of this paper is to assess different maintenance strategies and to select the best and the most appropriate alternatives for Saipa vehicle industry in Tehran, Iran. For this purpose, we simultaneously consider numerous conflicting objectives and constraints. In this study to counter with this conflicting and to consider the dependency among the qualitative and quantitative criteria and sub-criteria, an integration of Analytic Network Process (ANP) and fuzzy set theory are considered. Therefore, factors playing important role in selecting the best maintenance strategy are determined by reviewing the research literature and interviewing with the experts by Delphi technique. Considering the relations among different factors, a network with 4 criteria and 28 sub-criteria are proposed. In the next step, ANP technique is applied for ranking effective factors in evolution of appropriate maintenance strategy. Results reveal that the best maintenance strategy for fixture body of pride (setter) is corrective maintenance.