Order Picking Problem in a Warehouse with Bi-Objective Genetic Algorithm Approach: Case Study

Abstract

ABSTRACT:In this paper, an order picking problem with the capacitated forklift in a warehouse is studied by considering the total distance and the penalized earliness/tardiness. These objectives are important to reduce transportation costs and to satisfy customer expectations. Since this problem has been known as NP-hard, a genetic algorithm (GA) is proposed to solve the bi-objective order picking problem. The proposed approach is applied to auto components industry that produces wire harnesses responsible for all electrical functions in the vehicle. Experimental design is used for tuning the influential parameters of the proposed GA. The GA approach was solved by weighted sum scalarization.

Optimizing order-picking warehouse designs using collaborative robots

“…Kiriş vd. [53] sipariş-toplama için kat edilen toplam mesafeyi ve sipariş-toplama teslim zamanını minimize etmek için iki amaçlı bir model oluşturmuş ve GA ile oluşturdukları modeli çözmüşlerdir. Bottani vd.…”

Design of Warehouse Management System for Fresh Product in Supply Chain Network

“…Research related to warehousing and supply chain has so far discussed the use of RFID and WSN for perishable products even though it does not focus on fresh products [33][34] [35] [36] [37]. Research on decision support systems with genetic algorithms in warehouse management addresses layout and location allocation problems [38][39], order picking problems [40], optimization of item placement [41], production and distribution problems with multi factories for the same quality products [42]. But there has been no research that addresses the optimization of warehouse management with RFID and WSN using Algortima Genetics in SCN.…”