Paradox in a Linear Multi Objective Transportation Problem

Porchelvi, R. Sophia; Anitha, M.

doi:10.22457/apam.v15n2a4

Cited by 2 publications

(3 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Table 1 contains a comprehensive list of all 27 studies considered for inclusion. Fishery (20) [28]; [29]; [30] ; [31]; [32]; [33]; [34]; [35]; [36]; [37]; [38]; [39]; [40]; [41]; [42]; [43]; [13]; [44]; [45]; [46]; Aquaculture (13) [47] ; [48]; [49]; [6]; [50]; [51]; [52]; [53]; [54]; [55]; [56]; [57]; [58]; Fig. 1 The steps of the review Fig.…”

Section: B Selection Processmentioning

confidence: 99%

“…Disease management [48] ; [59]; [45] Scheduling and planning [51]; [40]; [60]; [33]; [52]; [61]; [55]; [56]; [22]; [44]; [62]; Harvest regulations [47]; [31]; [44] Sustainability [63]; [34]; [36]; [19]; [38]; [56]; [44]; [64] Catch optimization [28]; [29]; [6]; [65]; [39]; [54]; [42]; [13];…”

Section: Associated Dss Topic Documentmentioning

confidence: 99%

“…USING MACHINE LEARNINGSub DomainFisheries[29];[63];[34];[33];[66];[22];[57]; [13] Aquaculture[48];[47];[6];[50];[51];[54];[59] …”

unclassified

See 2 more Smart Citations

Decision Support System in Fisheries Industry: Current State and Future Agenda

Panudju¹,

Rahardja²,

Nurilmala³

et al. 2023

Int. J. Adv. Sci. Eng. Inf. Technol.

View full text Add to dashboard Cite

Decision Support Systems (DSS) are systems that assist decision-makers and aim to synthesize domain and technical knowledge and package it so non-scientists can use and comprehend it. This study aims to compile initial empirical studies that can objectively reject or confirm the central hypothesis. The materials were retrieved after applying the filtered query across all sources. All search engine providers use five query strings. In each example, five findings were collected, sorted, and compared to one another, and 152 papers were generated. Seventy-six documents were discovered after applying the inclusion and exclusion criteria. Each of the 70 papers was independently examined and analyzed. The method of study followed a specific procedure explicitly developed to minimize the risk of researcher bias. It is primarily concerned with whether fisheries have decision-making systems and what empirical outcomes these systems produce, particularly in real-time analysis. The result shows a dearth of research on intelligent DSS, which accounts for less than 3% of all DSS types discussed in the article. This study offers academics and professionals an overview of the implementation of DSS. These new contributions imply the form of several different new contributions to further research. Furthermore, the possibility of identifying research gaps increases once merged with geoinformation technology or spatial information. We introduced a new model that combines spatial logistics techniques with GIS-based tracing and tracking. The envisioned logistics ensure spatial and logistical traceability in the process of fish products.

show abstract