Synergic Effect of Reworking for Imperfect Quality Items with the Integration of Multi-Period Delay-in-Payment and Partial Backordering in Global Supply Chains

In intercontinental trade and economics goods are bought from a global supplier.On occasion,the expected lot may include a fraction of defective items.These imperfect items still have worth and can be sold to customers after repair.It is cost-effective and sustainable to rework such items in nearby repair workshops rather than return them.The reworked items can be returned from the workshop to the buyer when shortages are equal to the quantity of imperfect items.In the meantime,the supplier correspondingly deals a multi-period delay-in-payments strategy with purchaser.The entire profit has been maximized with paybacks for interim financing.This study aims to develop a synergic inventory model to get the most profit by making an allowance for reworking,multi-period delay-in-payments policy,and shortages.The findings of the proposed model augment inventory management performance by monitoring cycle time as well as fraction of phase with optimistic inventory for a supply chain.The results demonstrate that profit is smaller if the permitted period given by supplier to buyer is equal to or greater than the cycle time,and profit is greater if the permitted period is smaller than the cycle time.The algebraic method is engaged to make a closed system optimum solution.The mathematical experiment of this study is constructed to provide management insights and tangible practices.

Parallelization of a Branch and Bound Algorithm on Multicore Systems

The general m-machine permutation flowshop problem with the total flow-time objective is known to be NP-hard for m ≥ 2. The only practical method for finding optimal solutions has been branch-and-bound algorithms. In this paper, we present an improved sequential algorithm which is based on a strict alternation of Generation and Exploration execution modes as well as Depth-First/Best-First hybrid strategies. The experimental results show that the proposed scheme exhibits improved performance compared with the algorithm in [1]. More importantly, our method can be easily extended and implemented with lightweight threads to speed up the execution times. Good speedups can be obtained on shared-memory multicore systems.

Integrated schedule of order picking and delivery for instant delivery

In this study,we introduce an integrated schedule of order picking and delivery for instant delivery.Order picking,including order batching and picking sequencing,is scheduled online under real-time order arrival,which integrates order delivery by depicting order location dispersion in an online order picking strategy.Order delivery,including delivery person assignment and route planning,is modeled to minimize the total duration of order fulfillment by considering the influence of the order picking completion time.A rule-based online order picking strategy is established,and a customized ant colony optimization(ACO)algorithm is proposed to optimize order delivery.Experiments on 16 simulated instances of different scales demonstrate that our online order picking schedule considering order delivery outperforms existing approaches and that the customized ACO algorithm for order delivery is effective.

The impact of blockchain technology on consumer behavior:a multimethod study

Blockchain is a ground-breaking technology that is transforming supply chain management.This study aims to empirically investigate the impacts of blockchain technology on consumer behavior.We conduct this research in collaboration with a Chinese e-commerce company that has introduced a blockchain platform for tracing.We use a multimethod design by combining natural experiment-and case study methods.First,we collected data from four industries(i.e.milk powder,seafood,alcohol and nutrition)to conduct the experiment,and the findings reveal that the firms that adopted the blockchain tracing system have an increase in product sales and a decrease in product returns compared to those that did not.Second,we conducted a multiple case study with four cases from the four industries.The findings reveal that the adoption of a blockchain tracing system improves supply chain transparency and process management,which then enhances consumer service and trust.This study contributes to the literature by providing empirical evidence that adopting blockchain technology can improve firms’marketing performance.The findings also reveal how the adoption of blockchain technology affects consumer behavior.

Data mining-based algorithm for assortment planning

With increasing varieties and products,management of limited shelf space becomes quite difficult for retailers.Hence,an efficient product assortment,which in turn helps to plan the organization of various products across limited shelf space,is extremely important for retailers.Products can be distinguished based on quality,price,brand,and other attributes,and decision needs to be made about an assortment of the products based on these attributes.An efficient assortment planning improves the financial performance of the retailer by increasing profits and reducing operational costs.Clustering techniques can be very effective in grouping products,stores,etc.and help managers solve the problem of assortment planning.This paper proposes data mining approaches for assortment planning for profit maximization with space,and cost constraints by mapping it into well-known knapsack problem.