A decision-support framework for optimal shuttle bus electrification based on the knapsack problem

Date of Publication

6-2026

Document Type

Master's Thesis

Degree Name

Master of Science in Environmental Engineering and Management

Subject Categories

Engineering

College

Gokongwei College of Engineering

Department/Unit

Chemical Engineering

Thesis Advisor

Dr. John Frederick Tapia

Defense Panel Chair

Dr. Raymond R. Tan

Defense Panel Member

Dr. Carla Mae Pausta

Dr. Jose Bienvenido Manuel Biona

Abstract (English)

The shuttle service operations of Company A contribute to the total greenhouse gas (GHG) emissions of the company. To support its decarbonization initiatives, this study developed a decision-support framework for the implementation of phased electrification. The framework balances emission reduction goals with financial constraints to identify cost-effective electrification strategies under different operating scenarios. Total FY2025 shuttle bus emissions was estimated at 6,495.97 tCO₂e/year across 78 shuttle routes using a well-to-wheel approach. To evaluate electrification options, a knapsack optimization approach was applied under varying diesel price scenarios and emission reduction targets of 5%, 10%, 15%, and 20%. Six optimization models were developed to assess different implementation strategies, including electrification cost minimization, route clustering, charging infrastructure availability, total transportation cost minimization, and maximum achievable emission reduction under financial constraints. Results show that increasing diesel prices generally improve the cost-effectiveness of electrification, enabling higher emission reductions. Across the evaluated scenarios, Model 1 was identified as the most suitable planning tool for determining the least-cost electrification pathway, while Model 3 provided a more practical approach by incorporating charging infrastructure availability at destination sites into route selection. Consequently, this project demonstrates that a phased approach is a practical electrification strategy, as optimization can be used to determine the best combination of shuttle routes that satisfies emission reduction targets within a limited financial allocation. The developed framework serves as a data-driven tool for supporting environmental target setting and decarbonization planning.

Abstract Format

html

Abstract (Filipino)

Ang operasyon ng shuttle service ng Company A ay nakadaragdag sa greenhouse gas (GHG) emissions. Bilang suporta sa layunin nito sa dekarbonisasyon, bumuo ang pag-aaral na ito ng balangkas para sa unti-unting elektripikasyon, o pagpapalit ng mga diesel shuttle bus tungo sa mga electric shuttle bus. Layunin ng balangkas na balansehin ang mga target sa pagbabawas ng emisyon at mga limitasyong pinansyal upang matukoy ang estratehiyang episyente sa gastos sa iba’t ibang sitwasyon. Tinatayang umabot sa 6,495.97 tCO₂e bawat taon ang emisyon ng 78 shuttle routes noong FY2025 gamit ang well-to-wheel approach. Upang suriin ang mga opsyon sa elektripikasyon, ginamit ang knapsack optimization approach sa iba’t ibang sitwasyon ng presyo ng diesel at mga target sa pagbabawas ng emisyon na 5%, 10%, 15%, at 20%. Bumuo ang pag-aaral ng anim na modelo ng optimisasyon upang suriin ang mga estratehiya, kabilang ang pagpapababa ng gastos sa elektripikasyon, pagpapangkat ng mga ruta, pagkakaroon ng charging stations, at pagpapalaki ng pagbabawas ng emisyon sa loob ng limitasyong badyet. Ipinakita ng mga resulta na ang pagtaas ng presyo ng diesel ay nagpapabuti sa cost-effectiveness ng elektripikasyon at nagbibigay-daan sa mataas na pagbabawas ng emisyon. Sa mga sitwasyong sinuri, natukoy ang Model 1 bilang pinakaangkop para sa pagtukoy ng landas sa elektripikasyon na may pinakamababang gastos, habang ang Model 3 ay mas praktikal dahil isinasaalang-alang nito ang pagkakaroon ng charging stations sa destinasyon. Ipinapakita ng pag-aaral na ang unti-unting elektripikasyon ay praktikal na estratehiya para sa dekarbonisasyon at nagbibigay ng batayan sa pagpapatupad nito.

Abstract Format

html

Language

English

Format

Electronic

Keywords

Knapsack problem (Mathematics)

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