Additional resistance induced by shallow water effects is a critical factor influencing fuel economy during ship design and operation, especially in shallow sea areas such as the Baltic Sea. To address fuel efficiency challenges in such regions, this paper proposes a speed optimization model that accounts for shallow water resistance. The model adopts a multi-objective genetic algorithm integrated with a hypervolume indicator to optimize both total fuel consumption and voyage time. Three operational strategies are investigated: minimizing overall fuel consumption, applying shallow water resistance constraints, and maintaining constant optimal engine power. The effectiveness of each strategy is assessed on a typical Baltic route. Results show that the proposed optimization strategy can reduce fuel consumption by approximately 3.6% without compromising voyage schedules. Moreover, the additional fuel consumption attributed to shallow water effects can be limited to 2.5%. The proposed approach demonstrates strong effectiveness and engineering applicability, providing theoretical support and optimization guidance for green ship design and intelligent speed control.