An Optimization Model of a Sustainable City Logistics Network Design Based on Goal Programming

This paper investigates the joint optimization problem on logistics infrastructure investment and CO2 emission taxes for a sustainable city network design by goal programming approach where cost recovery, service level reduction goals are involved. The above multi-objective capacity is formulated as bi-level model. Given priority structure of goals, total deviations from predetermined minimized in upper level, while lower model serves route choice equilibrium users. To solve proposed model, genetic algorithm developed, method successive average (MSA) embedded. case study focusing urban Changsha, China demonstrates effectiveness algorithm. findings reveal that rankings have significant impact decisions investment. methodology provides an avenue to balance multiple conflicting objectives obtain economical environmental network.