English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

In this paper, we propose a method to solve a bi-objective variant of thewell-studied Traveling Thief Problem (TTP). The TTP is a multi-componentproblem that combines two classic combinatorial problems: Traveling SalesmanProblem (TSP) and Knapsack Problem (KP). We address the BI-TTP, a bi-objectiveversion of the TTP, where the goal is to minimize the overall traveling timeand to maximize the profit of the collected items. Our proposed method is basedon a biased-random key genetic algorithm with customizations addressingproblem-specific characteristics. We incorporate domain knowledge through acombination of near-optimal solutions of each subproblem in the initialpopulation and use a custom repair operator to avoid the evaluation ofinfeasible solutions. The bi-objective aspect of the problem is addressedthrough an elite population extracted based on the non-dominated rank andcrowding distance. Furthermore, we provide a comprehensive study showing theinfluence of each parameter on the performance. Finally, we discuss the resultsof the BI-TTP competitions at EMO-2019 and GECCO-2019 conferences where ourmethod has won first and second places, respectively, thus proving its abilityto find high-quality solutions consistently.

A Non-Dominated Sorting Based Customized Random-Key Genetic Algorithm for the Bi-Objective Traveling Thief Problem