The paper introduces HapSolo, a novel method designed to improve the assembly of diploid genomes by removing secondary haplotigs. HapSolo evaluates candidate primary assemblies using BUSCO scores and distinguishes among them using a cost function that can be defined by the user. The method performs hill climbing to minimize the cost over thousands of candidate assemblies. The authors demonstrate the effectiveness of HapSolo on three species: Chardonnay grape, Anopheles mosquito, and Thorny Skate, showing significant improvements in assembly metrics such as genome size and contig N50 scores. The benefits of HapSolo are further amplified by downstream analyses, particularly scaffolding with Hi-C data, leading to more contiguous genomes and improved scaffolded assemblies. HapSolo is implemented in Python and is freely available, offering a valuable tool for improving the assembly of highly heterozygous genomes.The paper introduces HapSolo, a novel method designed to improve the assembly of diploid genomes by removing secondary haplotigs. HapSolo evaluates candidate primary assemblies using BUSCO scores and distinguishes among them using a cost function that can be defined by the user. The method performs hill climbing to minimize the cost over thousands of candidate assemblies. The authors demonstrate the effectiveness of HapSolo on three species: Chardonnay grape, Anopheles mosquito, and Thorny Skate, showing significant improvements in assembly metrics such as genome size and contig N50 scores. The benefits of HapSolo are further amplified by downstream analyses, particularly scaffolding with Hi-C data, leading to more contiguous genomes and improved scaffolded assemblies. HapSolo is implemented in Python and is freely available, offering a valuable tool for improving the assembly of highly heterozygous genomes.