Adaptive Intertia Weight For A Hybrid PSO In Solving Multi-Objective CVRPTW In Air Freight Forwarding Segment: Ceva Logistics Case Study

Abstract

Capacitated Vehicle Routing Problem with Time Window which has been becoming a top consideration in forwarding segment. In order to decrease Air Door-To-Door cost when informing quotation for the customer, normal cargo (excluding Freeze and Hazardous Goods) should be consolidated before transport to the customer place. Following transportation issues, the concept of Fuzzy-Compromise Programming Method for the multi-objective optimization are used. In detail, this research employs Adaptive Inertia weight of Particle Swarm Optimization for directly interpretation of the Multi-Objective CVRPTW where both the total customers’ lead-time and total company’s cost are minimized while capacity and time windows constraints are still secured. The purpose of this work at utilizing a constraint programming for the problem formulation and an adaptive intertia weight of hybrid PSO to address it with simultaneously small size and large size problem of customer points.. The technical details requireds for this application are discussed. In this work, the proposed model is applied for CEVA Logistics Company Limited. Keywords: adaptive inertia weight of PSO, PSO algorithm, Time and Cost Optimization, FCPM.