A bi-level programming model and solution algorithm for the location of logistics distribution centers

In this paper, by considering benefits of customers and logistics planning departments, a bi-level programming model is presented to seek the optimal location for logistics distribution centers. The upper-level model is to determine the optimal location by minimizing the planners’ cost, and the lower gives an equilibrium demand distribution by minimizing the customers’ cost. Based on the special form of constraints, a simple heuristic algorithm is proposed. Finally, a numerical example is used to illustrate the application of the method, which shows that the algorithm is feasible and advantageous.     

Pricing used products for remanufacturing

Remanufacturing is one of recovery options for used products. As remanufacturing requires a continuous supply of used products, the economic incentive is required to attract customers to return their used products (called cores) and the problem of pricing a core becomes an important issue. Such a pricing problem is analogous to pricing an option, which can be used to sell the remanufactured cores (called core products). As sales price of core products follows a geometric Brownian motion, we propose a model here to evaluate the acquisition price of cores. This model links core acquisition price with the sale price of core product but assumes other costs such as logistics and remanufacturing to be deterministic. We have presented a numerical example to show its applicability. Since the model proposed here is generic, it is believed that the proposed model can be used in setting the core prices in many situations.     

A competitive dynamic pricing model when demand is interdependent over time

In this study, we contribute to the dynamic pricing literature by developing a finite horizon model for two firms offering substitutable and nonperishable products with different quality levels. Customers can purchase and store the products, even if they do not need them at the time, in order to use them in future. The stockpile of the products generated by customers affects the demand in future periods. Therefore, the demand for each product not only is a function of prices and quality levels, but also of the products’ stockpile levels. In addition, the stockpile levels change the customers’ consumption behavior; more product in a stockpile leads to more consumption. Therefore, we address not only the price and demand relationship but also the stockpiling and consumption relationship in a competitive environment.     

Interactive fuzzy goal programming for a multi-objective closed-loop logistics network

Over the last decade, there has been increased attention to closed-loop logistics networks. Environmental legislation requires companies to be more responsible by collecting used products from customers. Companies can also benefit from savings that are related to recovering and recycling used products. Unlike previous studies, which only consider single products or a single period of time in multi-objective problems, this paper considers a multi-product multi-period closed-loop logistics network with different types of facilities. A?multi-objective mixed-integer nonlinear programming formulation is developed to minimize the total cost, the delivery time of new products, and the collection time of used products. Thus, this model better approximates real-life applications of closed-loop logistics problems. Interactive fuzzy goal programming (IFGP) is applied to solve the model for handling multiple objective problems with conflicting objectives and to address the imprecise nature of decision-makers?? aspiration levels for goals. The results from computational experiments performed here show that by changing the upper or lower bound of each objective function, one can obtain a better final solution of the problem and also can provide more options for decision makers to choose from based on their situation. Finally, the utilization rate of facilities is shown to be an important indicator when designing a logistics network.     

考虑退货不确定性的多层次多站点逆向物流网络选址优化研究

在退货量不确定情况下,为追求电商企业逆向物流网络成本最小化,建立了多层次多站点的混合整数规划模型。将目标区域进行网格化处理,通过球上距离公式计算相邻备选站点、不同层次备选点间的运输距离,使用蒙特卡罗法模拟退货量,并设计了双染色体编码的遗传算法进行求解。算例验证了模型算法的可行性,并且得出了逆向物流网络成本最小时,快递站点和退货处理中心的选址,快递站点的选址与退货量大小存在对应关系,研究客户退货量会使物流网络选址得到优化。     

Pricing surplus server capacity for mean waiting time sensitive customers

We consider a queueing model wherein the resource is shared by two different classes of customers, primary (existing) and secondary (new), under a service level based pricing contract. This contract between secondary class customers and resource manager specifies unit admission price and quality of service (QoS) offered. We assume that the secondary customers’ Poisson arrival rate depends linearly on unit price and service level offered while the server uses a delay dependent priority queue management scheme. We analyze the joint problem of optimal pricing and operation of the resource with the inclusion of secondary class customers, while continuing to offer a pre-specified QoS to primary class customers. Our analysis leads to an algorithm that finds, in closed form expressions, the optimal points of the resulting non-convex constrained optimization problem. We also study in detail the structure and the non-linear nature of these optimal pricing and operating decisions.     

Product availability in competitive and cooperative dual-channel distribution with stock-out based substitution

This paper investigates the impact of customers’ stock-out based substitution on the product availability and the channel efficiency of a dual-channel supply chain, which consists of a supplier distributing a single product to customers through both its wholly owned direct channel and an independent retailer. The supplier and its retailer, with the objective of optimizing their own profit, simultaneously choose their own base-stock level to satisfy the stochastic demand from the customers whose channel preferences are heterogeneous and may be affected by each channel’s product availability. The customers dynamically substitute between the two channels in the event of a stock-out. The result shows that the effect of the stock-out based substitution may increase or decrease the efficiency of a decentralized supply chain. It is found that while the integrated supplier–retailer may consolidate the base-stock levels to benefit from stock-out based substitution, the independent supplier and retailer are more inattentive to customers’ stock-out based substitution. Thus, the competitive base-stock levels of the decentralized dual-channel supply chain rarely agree with the system optimal levels. Various contracts are examined to shed light on channel coordination mechanisms. In addition, it is shown that the channel efficiency of the dual-channel distribution can be improved by the emergence of Stackelberg leadership from either the supplier or the retailer.     

Dynamic pricing and warranty policies for products with fixed lifetime

We consider a repairable product with known market entry and departure times. A warranty policy is offered with product purchase, under which a customer can have a failed item repaired free of charge in the warranty period. It is assumed that customers are heterogeneous in their risk attitudes toward uncertain repair costs incurred after the warranty expires. The objective is to determine a joint dynamic pricing and warranty policy for the lifetime of the product, which maximizes the manufacturer’s expected profit. In the first part of the analysis, we consider a linearly decreasing price function and a constant warranty length. We first study customers’ purchase patterns under several different pricing strategies by the manufacturer and then discuss the optimal pricing and warranty strategy. In the second part, we assume that the warranty length can be altered once during the product lifetime in developing a joint pricing and warranty policy. Numerical studies show that a dynamic warranty policy can significantly outperform a fixed-length warranty policy.     

Dynamic pricing with two revenue streams

We study casino revenue management through the pricing of hotel rooms in the presence of gaming revenue, which is random. We identify a stochastic order based on customers’ gaming profiles, from which a monotonic inventory price of rooms is obtained. We develop a threshold-type pricing policy for a special customer segmentation scheme that allows customers’ winning profiles to be ranked in terms of the failure rate order. Our results shed new light on customer valuation and market segmentation.     

Integrated inventory models considering the two-level trade credit policy and a price-negotiation scheme

This paper develops the integrated inventory models with permissible delay in payment, in which customers’ demand is sensitive to the buyer’s price. The models consider the two-level trade credit policy in the vendor–buyer and buyer–customer relationships in supply chain management. A simple recursive solution procedure is proposed for the integrated models to determine the buyer’s optimal pricing and production/order strategy. Although the total profit from the buyer and vendor increases together, the buyer’s share lessens. To compensate the buyer’s loss due to the cooperative relationship, a negotiation system is presented in order to allocate the profit increase to the vendor and buyer to determine the pricing and production/order strategy. A numerical example and sensitivity analysis are provided to illustrate the proposed model. The results indicate that the total profit from the buyer and vendor together can increase, although a price discount is given to the buyer in the proposed models.     

Optimized appointment scheduling

In service systems, in order to balance the server’s idle times and the customers’ waiting times, one may fix the arrival times of the customers beforehand in an appointment schedule. We propose a procedure for determining appointment schedules in such a D/G/1-type of system by sequentially minimizing the per-customer expected loss. Our approach provides schedules for any convex loss function; for the practically relevant cases of the quadratic and absolute value loss functions appealing closed-form results are derived. Importantly, our approach does not impose any conditions on the service time distribution; it is even allowed that the customers’ service times have different distributions.     

When should service firms provide free experience service?

By providing a free experience service, a service firm can attract more uninformed customers. However, it could reversely effect the delay-sensitive, informed customers’ decision. In this paper, we study a priority queueing system with free experience services. We study the customer behavior in equilibrium after we derive the expected customer waiting time. We then construct the service firm’s revenue function and obtain an optimal strategy for the service firm. Our results suggest that when the market size of informed customers is relatively small, the firm should consider providing free experience services for uninformed customers. Conversely, if the demand rate of potential informed customers is quite high, the firm should ignore uninformed customers.     

Robust optimal dynamic production/pricing policies in a closed-loop system

Hybrid manufacturing/remanufacturing systems play a key role in implementing closed-loop production systems which have been considered due to increasingly environmental concerns and latent profit of used products. Manufacturing and remanufacturing rates, selling price of new products, and acquisition price of used products are the most critical variables to optimize in such hybrid systems. In this paper, we develop a dynamic production/pricing problem, in which decisions should be made in each period confronting with uncertain demand and return. The manufacturer is able to control the demand and return by adjusting selling price and acquisition price respectively, also she can stock inventories of used and new products to deal with uncertainties. Modeling a nominal profit maximization problem, we go through robust optimization approach to reformulate it for the uncertain case. Final robust optimization model is obtained as a quadratic programming model over discrete periods which can be solved by optimization packages of QP. A numerical example is defined and sensitivity analysis is performed on both basic parameters and parameters associated with uncertainty to create managerial views.     

A possibilistic-valued multi-criteria decision-making support for marketing activities in e-commerce: Feedback Based Diagnosis System

In this paper we propose a multi-criteria decision making support system, called a “Feedback Based Diagnosis System” (FBDS), to aid the marketing team of an e-commerce (EC) organisation in its activities. The FBDS database is composed of customers’ satisfaction measures. These measures are related to the different services an EC offers to its customers. Thus, they constitute a multi-criteria (MC) evaluation of EC performances. In the general framework of recommender systems, these available MC evaluations are considered as useful information for other customers to help them to objectively, rationally and exhaustively assess and compare the numerous ECs among the ones likely to meet their needs. Our FBDS is not concerned with improving or automating such a recommendation process for customers. Indeed, it is merely EC management team oriented. In fact, the MC feedback database is used to diagnose the EC health and improve its strategy. In the proposed FBDS, a possibilistic framework is combined with the multi criteria representation to capture the variability and the divergence of customers’ evaluations w.r.t. each criterion. Then, an aggregation based on a weighted arithmetic mean (WAM) is proposed to obtain a synthetic appraisal of ECs. The WAM aggregation models the strategy agreed on by the EC management team. Computing the synthesis score of an EC consists in propagating the uncertainty related to its partial scores through the WAM. The possibilistic representation guarantees that no information is lost in the collective evaluation process by the consumers’ community. However, diagnosis indicators are finally proposed to the marketing team to make the interpretation of some possibilistic results more comprehensive when necessary.     

A genetic algorithm for optimizing defective goods supply chain costs using JIT logistics and each-cycle lengths

The competitive environment of global markets has forced many manufacturers to select the most appropriate supply chain network (SCN) for reduction of total costs and wasted time. Cost reduction and selection of the appropriate length of each period are two important factors in the competitive market that are often not addressed comprehensively by researchers. In our study, we proposed genetic algorithms (GAs) for optimising a novel mathematical model of the defective goods supply chain network (DGSCN). In the proposed model, we assumed that all imperfect-quality products are not repairable, whereas those considered as scrap are directly sold to customers at a low price. The objective of the proposed model is to minimise the costs of production, distribution, holding and backorder. In addition to minimising the costs, the model can determine the economic production quantity (EPQ), the appropriate length of each cycle (ALOEC) and the quantities of defective products, scrap products and retailer shortages using Just-In-Time logistics (JIT-L). We used the GAs and a Cplex solver with probability parameters and various dimensions for validation of the studied model in real-life situations, and we compared the outputs to demonstrate the performance of the model. Additionally, to identify the appropriate length of each cycle (ALOEC), we needed to solve the model using exact parameters and same dimensions and prefer to use Lingo for this application.     

The effects of the availability of waiting-time information on a balking queue

We consider two balking queue models with different types of information about delays. Potential customers arrive according to a Poisson process, and they decide whether to stay or balk based on the available delay information. In the first model, an arriving customer learns a rough range of the current queue length. In the second model, each customer’s service time is the sum of a geometric number of i.i.d. exponential phases, and an arriving customer learns the total number of phases remaining in the system. For each information model, we compare two systems, identical except that one has more precise information. In many cases, better information increases throughput and thus benefits the service provider. But this is not always so. The effect depends on the shape of the distribution describing customers’ sensitivities to delays. We also study the effects of information on performance as seen by customers. Again, more information is often good for customers, but not always.     

Bundling decisions in supply chains

Firms often sell products in bundles to extract consumer surplus. While most bundling decisions studied in the literature are geared to integrated firms, we examine a decentralized supply chain where the suppliers retain decision rights. Using a generic distribution of customers’ reservation price we establish equilibrium solutions for three different bundling scenarios in a supply chain, and generate interesting insights for distributions with specific forms. We find that (i) in supply chain bundling the retailer’s margin equals the margin of each independent supplier, and it equals the combined margin when the suppliers are in a coalition, (ii) when the suppliers form a coalition to bundle their products the bundling gain in the supply chain is higher and retail price is lower than when the retailer bundles the products, (iii) the supply chain has more to gain from bundling relative to an integrated firm, (iv) the first-best supply chain bundling remains viable over a larger set of parameter values than those in the case of the integrated firm, (v) supplier led bundling is preferable to separate sales over a wider range of parameter values than if the retailer led the bundling, and (vi) if the reservation prices are uniformly distributed bundling can be profitable when the variable costs are low and valuations of the products are not significantly different from one another. For normally distributed reservation prices, we show that the bundling set is larger and the bundling gain is higher than that for a uniform distribution.     

Rental price and rental duration under retail competition

Consider a retailer that rents products to customers for a pre-specified rental duration. By considering the dynamics of uncertain rental demand and return processes, we first present a base model that is intended to analyze the impact of rental duration on the stocking level, the rental price, and the retailer’s profit. Due to the complexity of the base model, we develop an approximation scheme to obtain tractable results. Also, we apply the base model to analyze a situation in which a retailer enters a revenue sharing agreement with a distributor. Moreover, we expand our base model to address the issue of competition in rental duration and rental price. The analysis of our competitive model in a duopolistic environment suggests that the market equilibrium depends on the market potential and the rental duration sensitivity. Furthermore, we establish conditions under which one firm will charge a lower rental price while the other firm will offer a longer rental duration in equilibrium.     

A general variable neighborhood search for the one-commodity pickup-and-delivery travelling salesman problem

We present a variable neighborhood search approach for solving the one-commodity pickup-and-delivery travelling salesman problem. It is characterized by a set of customers such that each of the customers either supplies (pickup customers) or demands (delivery customers) a given amount of a single product, and by a vehicle, whose given capacity must not be exceeded, that starts at the depot and must visit each customer only once. The objective is to minimize the total length of the tour. Thus, the considered problem includes checking the existence of a feasible travelling salesman’s tour and designing the optimal travelling salesman’s tour, which are both NP-hard problems. We adapt a collection of neighborhood structures, k-opt, double-bridge and insertion operators mainly used for solving the classical travelling salesman problem. A binary indexed tree data structure is used, which enables efficient feasibility checking and updating of solutions in these neighborhoods. Our extensive computational analysis shows that the proposed variable neighborhood search based heuristics outperforms the best-known algorithms in terms of both the solution quality and computational efforts. Moreover, we improve the best-known solutions of all benchmark instances from the literature (with 200 to 500 customers). We are also able to solve instances with up to 1000 customers.     

An integrated product returns model with logistics and marketing coordination

We develop an integrated approach for analyzing logistics and marketing decisions within the context of designing an optimal returns system for a retailer servicing two distinct market segments. At the operational level, we show that the optimal refund price is not unique. Moreover, it is such that if both market segments return a purchased product, then neither segment will receive a full money-back refund; and it is such that if one or both segments do not return a purchased product, then a refund premium over the purchase price is possible, but the refund premium will not be enough to offset a customer's total net cost of purchase and return. We also show that any improvement to the returns system that results in increased logistical efficiency or marketing effectiveness will be accompanied by an increase in the selling price of the product. At the strategic level, we show that if the retailer does not coordinate its logistics and marketing efforts to improve the overall returns system, then it will tend to over-invest in one of the functions and under-invest in the other. Finally, we illustrate how our model can be generalized to the case in which a customer's ex post valuation of the product falls along a continuum.