Maximization of container slot booking profits for carriers in the liner shipping industry

In the liner shipping industry, if a shipper wants to transport its cargo by container ships, it first needs to contact a carrier to book container slots based on the estimated transportation demand. However, one problem in the booking process is that the actual demand is uncertain, resulting in mismatch between the required demand and the booked quantity. To address this issue, this study develops a Newsvendor model to find the optimal order quantity of container slots for the shipper. In addition, uncertainties in the quantity of container slots booking made by the shipper might cause revenue loss to the carrier and low utilization of ship capacity in the daily operations of liner shipping services. Therefore, this study suggests that the shipper should pay reservation fee when booking container slots. This study also aims to find the maximum profit for the carrier under the optimal order quantity of the shipper. In sensitive analysis, how different prices per container slot offered by the carrier would influence the reservation fee, the optimal order quantity of the shipper, and the expected profit of the carrier are explored and discussed. This study can help to manage and promote the online container booking systems in the liner shipping industry.

Trade Credit with Barter in a Capital-Constrained Supply Chain

Barter has emerged to alleviate capital pressure, maximize the circulation of goods, and facilitate the disposal of excess inventory. This study considers a two-level supply chain consisting of a manufacturer and a capital-constrained retailer with trade credit, in which the retailer exchanges unsold products for needed subsidiary products on a barter platform. The retailer’s optimal order quantity and the manufacturer’s wholesale price are derived, and the influences of barter and other factors on the equilibrium strategy and performance of the supply chain are examined; these results are verified and supplemented by numerical simulation. We find that the retailer can increase profit by bartering when facing highly uncertain demand, that the retailer’s optimal order quantity increases with the supply rate and demand for subsidiary products, and that both manufacturer and retailer benefit from the high supply rate of subsidiary products. However, barter induces the manufacturer to raise the wholesale price to prevent its profit from being harmed. In addition, the manufacturer suffers from the retailer’s initial capital.

Multi-Period Age-Discriminated Perishable Inventory

In this paper, an extremely short shelf-life inventory of age-discriminated stochastic demand is considered. Age discriminated demand can be found in products of high circulation and short shelf-lives such as dairy products, packaged food, pharmaceutical products and medical products of short shelf lives. Simulation based optimization is considered to find the optimal order quantity. The model employs Discrete Event Simulation along with a modified simulated annealing algorithm. To validate the model and the optimization algorithm, the classical newsvendor problem is tested first, later, different experiments are carried out for different product lifetimes. In contrast to the classical newsvendor, this problem tackles a multi-period inventory of different ages and different demand distributions. The objective is to determine the optimal order quantity to satisfy the stochastic demand of all ages such that shortages and expirations are minimized. The results showed remarkable performance and outstanding minimum levels of shortage and expiration.

Coping with Loss Aversion and Risk Management in the Supply Chain Coordination

In this paper, we apply a combined revenue sharing and buyback contract to investigate the channel coordination of a two-echelon supply chain with a loss-averse retailer. Since loss-averse decision makers usually take on more risks, the Conditional Value-at-Risk (CVaR) measure is introduced to hedge against it and the retailer’s objective is to maximize the CVaR of utility. We obtain the retailer’s optimal order quantity under the combined contract. It is shown that there is a unique wholesale price coordinating the supply chain if the retailer’s confidence level is less than a threshold that is independent of contract parameters. Moreover, a complete sensitivity analysis of parameters is carried out. In particular, the retailer’s optimal order quantity and coordinating wholesale price decreases as the loss aversion or confidence level increases, while it increase as the buyback price or sharing coefficient increases. Furthermore, there exists the situation where the combined contract can coordinate the chain even though neither the revenue sharing nor buyback contract can when the contract parameters are constrained.

PENGENDALIAN PERSEDIAAN PROBABILISTIK PRODUK SUBSTITUSI DENGAN PERMINTAAN SEBAGAI FUNGSI HARGA

Kamara Living merupakan suatu unit usaha yang bergerak dalam penjualan kebutuhan sehari-hari. Salah satu produk yang populer adalah sarung bantal. Sarung bantal yang ditawarkan memiliki beberapa desain motif dan jenis yang berbeda. Permintaan akan produk sarung bantal tidak menentu antara satu desain dengan desain yang lain. Ketika desain tertentu persediaannya habis, perusahaan akan menawarkan desain lain dari jenis kain yang sama. Jika konsumen tidak bersedia maka terjadi kehilangan penjualan. Ketika persediaan berlebih, perusahaan akan memberikan harga promosi untuk mendongkrak tingkat penjualannya. Jika ini dibiarkan terus-menerus, tentu saja perusahaan akan mengalami penurunan keuntungan. Pada makalah ini dikembangkan model persediaan dengan mempertimbangkan produk substitusi dengan permintaan sebagai fungsi harga yang bertujuan untuk meminimasi total biaya persediaan. Penyelesaian model yang dilakukan mampu menghasilkan solusi kuantitas pemesanan dan titik pemesanan yang optimal. Validasi model dilakukan dengan membandingkan hasil dari model yang dikembangkan terhadap kondisi riil. Selain itu juga dilakukan analisis sensitivitas terhadap parameter-parameter yang berpengaruh. Abstract[Product-substitution Inventory Model with Demand depend on Price] Kamara Living is a business unit engaged in selling daily stuff. One popular product is pillowcases. The pillow cover offered has several different motif designs and types. The demand for pillowcases is uncertain between one design and another. When a stockout occurs for a particular design, the company will offer another design of the same type of fabric. If consumers are not willing, there will be lost sales. When there is overstock, the company will provide promotional prices to increase sales levels. If this is allowed to continue, of course the company will experience a decline in profits. In this paper, an inventory model is developed by considering substitute products with demand as a price function that aims to minimize the total cost of inventory. Completion of the model carried out is able to produce optimal order quantity and order point solutions. Model validation is done by comparing the results of the models developed against real conditions. In addition, a sensitivity analysis was carried out on the influential parameters.Keywords: Inventory Models; Product Substitution; Demand Depend on Price

Coordination model of supply chain based on deciders’ risk attitudes in a fuzzy decision environment

This paper considers a two-stage supply chain consisting of one manufacturer and one retailer, exploring the impact of the fuzzy uncertainty of product yield and demand and the deciders’ risk attitudes on the optimal order quantity of the retailer. At the same time, this study tries to analyze the coordination problem in the two-stage supply chain with consideration of the retailer and the manufacturer’s risk attitudes. Firstly, this study develops a supply chain optimal decision model in a centralized decision framework. In the proposed model, the L-R fuzzy numbers are used to depict the yield and demand with fuzzy characteristics. Then, the coordination of quantity discount in a supply chain is studied. Consequently, this research further investigates a special case in which the market demand and yield are assumed to be triangular fuzzy numbers, and the optimal solution of the order quantity and the wholesale price are obtained. At last, this paper utilizes several numerical examples to validate the proposed model. The results show that the quantity discount contract can coordinate the supply chain in a fuzzy environment, and the optimal order quantity decreases with the increasing of the risk bias coefficient of the retailer and the manufacturer. It also suggests that risk-seeking retailer will order more products, in addition, the manufacturer tend to choose a risk-seeking retailer as partner and the retailer is more likely to choose a risk-seeking rather than risk-aversion manufacturer as partner.

Fuzzy random Newsboy problem with chance distribution

Due to increasing difficulty and challenging issues of newsboy problem under uncertainty, managers seek newer and appropriate approaches to apprehend more accurately the demand for perishable products and or the products having a short shelf life. This paper investigates a newsboy problem with fuzzy random demand in a single product business scenario. The classical newsboy model is extended to a fuzzy random newsboy problem to determine the optimal order quantity and expected profit under hybrid uncertainty. To solve the proposed model, a new solution approach based on chance constraint programming is proposed to formulate the crisp equivalent form of the fuzzy random newsboy model. Numerical examples and a real-life case study are presented to show the utility of the projected model. From the outcomes, decision makers can make comprehensive recommendations for the optimal order quantity and expected profit obtained by our proposed model under two-folded uncertainty. Also, a sensitivity analysis suggests that the profit and order quantity will increase (or decrease) with the increase (or decrease) of the mean demand.