Location optimization of fresh food e-commerce front warehouse

The ongoing emergence of COVID-19 and the maturation of cold chain technology, have aided in the rapid development of the fresh produce e-commerce industry. Taking into account the characteristics of consumers' demand for fresh products, this paper constructs a location allocation model of a front warehouse for fresh e-commerce with the objective of minimizing the total cost. An improved immune optimization algorithm is proposed in this paper, and the effectiveness of the proposed algorithm is demonstrated by a real case study. The results show that the improved immune optimization algorithm outperforms the traditional genetic algorithm in terms of solution accuracy; the proposed location model can effectively help fresh produce e-commerce enterprises open new front-end warehouses when demand is increasing, as well as provide optimal economic decision-making for front warehouse layout

Skewed general variable neighborhood search for the location routing scheduling problem

The integrated location routing scheduling problem is a variant of the well-known location routing problem. The location routing problem consists in selecting a set of depots to open and in building a set of routes from these depots, to serve a set of customers at minimum cost. In this variant, a vehicle can perform more than a single route in the planning period. As a consequence, the routes have to be scheduled within the workdays of each vehicle. The problem arises typically when routes are constrained to have a short duration. It happens for example within the boundaries of small geographic areas or in the transportation of perishable goods. In this paper, we propose a skewed general variable neighborhood search based heuristic to solve it. The algorithm is tested extensively and we show that it is efficient and provides the proven optimal solution in a significant number of cases. Moreover, it clearly outperforms a multi-start VND based heuristic that uses the same neighborhood structures.Centre National de la Recherche Scientifique (CNRS), by the International Campus on Safety and Intermodality in Transportation (CISIT), by the Laboratoire d׳Automatique, de Mécanique et d׳Informatique industrielles et Humaines (LAMIH) of the Université de Valenciennes et du Hainaut-Cambrésis, by FEDER funding through the Programa Operacional Factores de Competitividade - COMPETE and by National funding through the Portuguese Science and Technology Foundation (FCT) in the scope of the project PTDC/EGE-GES/116676/2010 (Ref. COMPETE: FCOMP-01-0124-FEDER-020430) and through the grant SFRH/BPD/78024/2011. National Research University Higher School of Economics and supported by RSF Grant 14-41-00039., info:eu-repo/grantAgreement/FCT/5876-PPCDTI/116676/P