thitinon srisuwandee

Mr. thitinon srisuwandee

industrial engineering, ubonratchatani university, Ubon Ratchathani, Thailand
orcid

Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 November 2025 in Artificial Intelligence in Medicine
Verified
Journal Article
Closed access
Chutchai KaewtaChutchai Kaewta
Chutchai Kaewta
Rapeepan PitakasoRapeepan Pitakaso
Rapeepan Pitakaso
Surajet KhonjunSurajet Khonjun
Surajet Khonjun
Thanatkij SrichokThanatkij Srichok
Thanatkij Srichok
PLPeerawat luesak
Peerawat luesak
TSthitinon srisuwandee
thitinon srisuwandee

8 January 2023 in Computation
Verified
Journal Article
Open access
PDF file
TSThitiworada Srisuwandee
Thitiworada Srisuwandee
SSSombat Sindhuchao
Sombat Sindhuchao
TSthitinon srisuwandee
thitinon srisuwandee
The disposal of infectious waste remains one of the most severe medical, social, and environmental problems in almost every country. Choosing the right location and arranging the most suitable transport route is one of the main issues in managing hazardous waste. Identifying a site for the disposal of infectious waste is a complicated process because both tangible and intangible factors must be considered together, and it also depends on various rules and regulations. This research aims to solve the problem of the size selection and location of infectious waste incinerators for 109 community hospitals in the upper part of northeastern Thailand by applying a differential evolution algorithm to solve the problem with the objective of minimizing the total system cost, which consists of the cost of transporting infectious waste, the fixed costs, and the variable cost of operating the infectious waste incinerator. The developed differential evolution produces vectors that differ from the conventional differential evolution. Instead of a single set of vectors, three are created to search for the solution. In addition to solving the problem of the case study, this research conducts numerical experiments with randomly generated data to measure the performance of the differential evolution algorithm. The results show that the proposed algorithm efficiently solves the problem and can find the global optimal solution for the problem studied.

25 April 2025 in Intelligent Systems with Applications
Verified
Journal Article
Open access
PEPrem Enkvetchakul
Prem Enkvetchakul
Surajet KhonjunSurajet Khonjun
Surajet Khonjun
Rapeepan PitakasoRapeepan Pitakaso
Rapeepan Pitakaso
Thanatkij SrichokThanatkij Srichok
Thanatkij Srichok
PLPeerawat luesak
Peerawat luesak
TSthitinon srisuwandee
thitinon srisuwandee

20 May 2026 in Expert Systems with Applications
Verified
Journal Article
Closed access
JKJakrapong Krittiwattanapong
Jakrapong Krittiwattanapong
Rapeepan PitakasoRapeepan Pitakaso
Rapeepan Pitakaso
TSThanatkij Srichok
Thanatkij Srichok
SKSurajet Khonjun
Surajet Khonjun
CKChutchai Kaewta
Chutchai Kaewta
TSthitinon srisuwandee
thitinon srisuwandee