Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment Problem

Abstract

The Vehicle Routing Problem (VRP) and its variants are found in many fields, especially logistics. In this study, we introduced an adaptive method to a complex VRP. It combines multi-objective optimization and several forms of VRPs with practical requirements for an urban shipment system. The optimizer needs to consider terrain and traffic conditions. The proposed model also considers customers’ expectations and shipper considerations as goals, and a common goal such as transportation cost. We offered compromise programming to approach the multi-objective problem by decomposing the original multi-objective problem into a minimized distance-based problem. We designed a hybrid version of the genetic algorithm with the local search algorithm to solve the proposed problem. We evaluated the effectiveness of the proposed algorithm with the Tabu Search algorithm and the original genetic algorithm on the tested dataset. The results show that our method is an effective decision-making tool for the multi-objective VRP and an effective solver for the new variation of VRP.

Optimizing Heterogeneous Vehicle Routes for Urban Distribution Considering the Three-Dimensional Bin Packing Problem of Electric Meters

“…3L-CVRP not only takes into account the path optimization and load constraints in traditional VRP, but also additionally considers the threedimensional loading of goods, making it more challenging in solution design and optimization. The 3L-CVRP, considering the specific requirements related to electric meters, can be effectively divided into two sub-problems: the Urban VRP [18] and 3DBPP for electric meters. The Urban VRP can be succinctly characterized as a VRP subject to multiple constraints, a classic NP-hard problem.…”

Multi-Objective Decision Support for Irrigation Systems Based on Skyline Query

“…Under the 50~75% water supply rates, the algorithm chose to maintain irrigation to the three main branches (Branches 1, 22, and 38) and gradually reduce irrigation to the branches so as to ensure the most efficient allocation of water resources. Interestingly, over half of the solutions chosen by the target approach do not prioritize irrigation to the wider upstream branches but rather focus on the downstream branches as the main subjects of irrigation ( Branches 23,26,27,30,39,40,41,42,45,46,etc.). This contrasts strongly with traditional approaches to prioritize upstream over downstream to reduce water resource divergence.…”

“…Thus, heuristic algorithms can find near-optimal solutions that satisfy the objective conditions within a reasonable amount of time. For example, Ngo et al [39] proposed compromise programming to approach the multi-objective problem by decomposing the original multiobjective vehicle routing problem into a minimized distance problem. They then used a hybrid version of the genetic algorithm with a local search algorithm to obtain solutions.…”

Mission Analysis of Small-Scale LNG Carrier as Feeder for East Indonesia: Ambon City as the Hub Terminal

“…This scheduling and planning process needs to be calculated before the actual operation. The necessity to coordinate several resources, including machinery, trucks, and other fleets, makes this a difficult task 9) . The distribution system cannot be separated from the company's business processes, planning the sequence of product distribution routes from sources or hubs.…”