A teaching–learning-based optimization algorithm for the environmental prize-collecting vehicle routing problemA teaching–learning-based optimization algorithm for the environmental prize-collecting vehicle routing problem Peer-Reviewed Journal Publication Δημοσίευση σε Περιοδικό με Κριτές 2023-05-022021enThis research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme: Human Resources Development, Education and Lifelong Learning, in the context of the project “Strengthening Human Resources Research Potential via Doctorate Research” (MIS-5000432), implemented by the State Scholarships Foundation (IKY) (Nos. 2018-050-0502-13964, 2018-050-0502-13953).The present research proposes a new Vehicle Routing Problem (VRP) variant, the Environmental Prize-Collecting Vehicle Routing Problem (E-PCVRP). According to the original PCVRP formulation, the scope of the problem is to maximize the total collected prize from the visited nodes and simultaneously minimize the fixed vehicle-utilization cost and the variable cost. In the E-PCVRP formulation, the variable cost is not solely expressed as a vehicle-covered distance but as a load-distance function for CO2 emissions minimization. The Teaching–Learning-Based Optimization (TLBO) algorithm is selected as the solution approach. However, TLBO is designed to address continuous optimization problems, while the solution of the E-PCVRP requires a discrete-numbered representation. Thus, a heuristic encoding/decoding technique is proposed to map the solution in a continuous domain, i.e., the Cartesian space, and transform it back to the original form after applying the learning mechanisms, utilizing the Euclidean Distance. The encoding/decoding process is denoted as CRE, and it has been incorporated into the standard TLBO algorithmic scheme, and as such, the proposed TLBO-CRE algorithmic solution approach emerges. The effectiveness of the TLBO-CRE is demonstrated over computational experiments and statistical analysis in comparison to the performance of other bio-inspired algorithms and a mathematical solver.http://creativecommons.org/licenses/by/4.0/Energy Systems Trachanatzi Dimitra Τραχανατζη Δημητρα Rigakis Manousos Ρηγακης Μανουσος Marinaki Magdalini Μαρινακη Μαγδαληνη Marinakis Ioannis Μαρινακης Ιωαννης Springer Teaching–learning-based optimization algorithm Prize-collecting vehicle routing problem Environmental vehicle routing problem Carbon emissions minimization