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We consider a production–inventory queueing system consisting of a queue and an inventory, where there is a single type of product and a single firm. Customers can observe the number of products in the inventory and the number of waiting customers in the queue upon arrival. Customers decide whether to wait for the product or leave without a purchase according to their utility, which depends on the product's price and estimated waiting time. If the number of products in the inventory is lower than a certain threshold, the firm produces the products. The product's production time and the customers' reward from purchasing the product have general distributions. We investigate the customers' equilibrium strategies, profit maximization and social welfare maximization. Specifically, we show that a customer's equilibrium strategy exists for a given joint pricing and inventory control. In general, there can exist multiple equilibria. However, if the production time distribution is decreasing mean residual life, the equilibrium is unique. We also present a method for computing equilibrium strategies. In addition, we compute the maximum profit rate and the profit-maximizing solution. We also compute the maximum social benefit rate and the welfare-maximizing solution. Finally, we present various numerical experiments that include comparisons of the maximum profit rate and the maximum social benefit rate, as well as of the profit-maximizing solution and the welfare-maximizing solution. [ABSTRACT FROM AUTHOR]

Letter of credit (LC) plays an important role in supporting financial activities and facilitating transactions in supply chain finance. An LC provides an option for advance payment by shippers (buyers) to exporters (suppliers). The payment is made by financial companies. For risk management, financial companies usually require shippers to insure their goods. The selection of shipping port designations and transshipment ports is a commonly listed LC clause. Thus, a container port could consider providing shipping insurance subsidies along with the quality port service to attract shippers. Recently, facility sharing (FS) has been adopted by the Hong Kong Port (HKP) to reduce operating costs at terminals. We study the shipping insurance subsidies provided to shipper by the HKP utilising the benefits of FS. Our research is based on real-life data. We propose an insurance incentive strategy (IIS) as a profit maximisation problem and examine the relationship between the optimal capacity for transshipment, insurance rate, FS cost savings, and benefits of the IIS. Our results demonstrate that the IIS could lead to a win–win situation for shippers and container ports. We observed that the IIS could reduce the risk in supply chain finance and strengthen the partnership between port operators, liners, shippers, financial companies, and insurance companies. The total shipping insurance cost can be reduced with improved credibility and economies of scale. We also discuss different scenarios that are particularly desirable for the adoption of IIS. [ABSTRACT FROM AUTHOR]

The need for a study of project portfolio optimization in pharmaceutical R&D has become all the more urgent with the outbreak of COVID-19. This study examines a new model for optimizing R&D project portfolios under a decentralized decision-making structure in a pharmaceutical holding company. Specifically, two levels of decision makers hierarchically decide on budget allocation and project portfolio selection-scheduling to maximize their profit, and we formulate the problem as a bi-level multi-follower mixed-integer optimization model. At the upper level, the investment company has complete knowledge of the subsidiaries' response, acts first, and decides on the best budget allocation. At the lower level, each subsidiary responds to the allocated budget and decides on its portfolio scheduling. Since the lower level represents several mixed-integer programming problems, solving the resulting bi-level model is challenging. Therefore, we propose an efficient hybrid solution approach based on parametric optimization and convert the bi-level model into a single-level mixed-integer model. To validate it, we solve a case and discuss the optimal strategy of each actor. The experimental results show that the planned project portfolio for each subsidiary of the holding company is drastically affected by the allocated budget and its decisions. [ABSTRACT FROM AUTHOR]

One of the key issues in transportation systems is allocating shipping orders to the most appropriate drivers in the shortest time and with the maximum profit. Many studies were carried out in the transportation service procurement process for allocating orders, but none of them considered driver-to-driver interactions and applied information diffusion concepts as a framework to maximize the profit, due to the lack of a framework to model the interactions. In this paper, we present a weighted drivers' collaboration network to form the interactions. To predict the behavior of drivers, a new community detection algorithm is developed to extract communities and their leaders in terms of the speed and power of receiving and diffusing shipping orders. In addition, we present a profit maximization model that utilizes the information diffusion power of community leaders. The results show the model is able to allocate shipping orders to the most suitable drivers in the shortest possible time and with the highest profit. To demonstrate the performance of the developed algorithm, we present a numerical example. Finally, a case study is applied to solve the optimization problem. The results show that the optimized behavior of companies in allocating orders to drivers is based on their risk level, reputation, and the average number of their customers. [ABSTRACT FROM AUTHOR]

Small farmers in emerging economies face numerous constraints, including financial distress and limited access to profitable markets. Thus, procurement contracts having provisions for resource inputs are essential in linking them to the mainstream agri-supply chains. Consequently, we frame a decision-making model for a risk-neutral firm offering advance payment contracts to such credit-constrained smallholders. The firm allows them to commit their supply quantities and pays a fraction of the per-unit guaranteed price for the crop as advance. Behaviorally, the decision-biased farmers are loss-averse and hyperbolic discounters. They have a subjective perception of crop yield based on the (timing of) advance. Our model establishes a criterion for the firm to shortlist the farmers for contracting. Subsequently, it predicts their commitment quantities under limited information on their behavioral parameters using the Prospect Theory framework. Under the model assumptions, we calculate the upper and lower bounds on their commitment quantities, thereby establishing the limits on the firm's production quantity and profitability. Lastly, our model determines the optimal timing for paying the advances to the eligible farmers using two different strategies. The first favors a firm's profit maximization objective, while the second maximizes its marginal cost savings from contracting over spot buying. Through analytical and numerical calculations, we establish that the latter approach significantly raises the farmers' utilities without severely affecting the firm's profit. Thus, making it fit for a social entrepreneur on a mission to create a socially responsible and economically viable procurement strategy. [ABSTRACT FROM AUTHOR]

This paper addresses a supply chain situation, in which a company distributes commodities over a selected subset of customers while a manufacturer produces the commodities demanded by the customers. The distributor company has two objectives: the maximization of the profit gained by the distribution process and the minimization of CO 2 emissions. The latter is important due to the regulations imposed by the government. A compromise between both objectives exists, since profit maximization only will attempt to include as many customers as possible. But, longer routes will be needed, causing more CO 2 emissions. The manufacturer aims to minimize its manufacturing and shipping costs. Since a predefined hierarchy between both companies exists in the supply chain, a bi-level programming approach is employed. This problem is modelled as a bi-level programming problem with two objectives in the upper level and a single objective in the lower level. The upper level is associated with the distributor, while the lower level is associated with the manufacturer. Due to the inherent complexity to optimally solve this problem, a heuristic scheme is proposed. A nested bi-objective tabu search algorithm is designed to obtain non-dominated bi-level feasible solutions regarding the upper level. Considering simultaneously both objectives of the distributor allow us to focus on the minimization of CO 2 emissions caused by the supply chain, but bearing in mind the distributor's profit. Numerical experimentation shows that the Pareto frontiers obtained by the proposed algorithm provide good alternatives for the decision-making process and also, some managerial insights are given. [ABSTRACT FROM AUTHOR]

In this paper, an inventory problem where the inventory cycle must be an integer multiple of a known basic period is considered. Furthermore, the demand rate in each basic period is a power time-dependent function. Shortages are allowed but, taking necessities or interests of the customers into account, only a fixed proportion of the demand during the stock-out period is satisfied with the arrival of the next replenishment. The costs related to the management of the inventory system are the ordering cost, the purchasing cost, the holding cost, the backordering cost and the lost sale cost. The problem is to determine the best inventory policy that maximizes the profit per unit time, which is the difference between the income obtained from the sales of the product and the sum of the previous costs. The modeling of the inventory problem leads to an integer nonlinear mathematical programming problem. To solve this problem, a new and efficient algorithm to calculate the optimal inventory cycle and the economic order quantity is proposed. Numerical examples are presented to illustrate how the algorithm works to determine the best inventory policies. A sensitivity analysis of the optimal policy with respect to some parameters of the inventory system is developed. Finally, conclusions and suggestions for future research lines are given. [ABSTRACT FROM AUTHOR]

Supply chain disruptions compel professionals all over the world to consider alternate strategies for addressing these issues and remaining profitable in the future. In this study, we considered a four-stage global supply chain and designed the network with the objectives of maximizing profit and minimizing disruption risk. We quantified and modeled disruption risk as a function of the geographic diversification of facilities called supply density (evaluated based on the interstage distance between nodes) to mitigate the risk caused by disruptions. Furthermore, we developed a bi-criteria mixed-integer linear programming model for designing the supply chain in order to maximize profit and supply density. We propose an interactive fuzzy optimization algorithm that generates efficient frontiers by systematically taking decision-maker inputs and solves the bi-criteria model problem in the context of a realistic example. We also conducted disruption analysis using a discrete set of disruption scenarios to determine the advantages of the network design from the bi-criteria model over the traditional profit maximization model. Our study demonstrates that the network design from the bi-criteria model has a 2% higher expected profit and a 2.2% lower profit variance under disruption than the traditional profit maximization solution. We envisage that this model will help firms evaluate the trade-offs between mitigation benefits and mitigation costs. [ABSTRACT FROM AUTHOR]

Nowadays green retail practices are increasing in number. In this paper, an inventory model is formulated with retail investments in green operations including variable holding cost. In the proposed model, the demand rate depends on selling-price as well as green concern level. The main objective of the study is to find optimal replenishment time and optimal green concern level by considering profit maximization. Here, the effect of greening-level on purchasing-price and selling-price is shown. By investing in green operations, a retailer creates considerable impact on profitability. As the greening level increases, the profit of a retailer increases. Product with lower deterioration rate would increase the profit. Based on the above consideration, the mathematical model is designed by allowing carbon tax. Then, the model is explored by numerical examples. Mathematica software is used to obtain global maximum solution to the optimal cycle time and optimal greening-level. A sensitivity analysis with respect to major parameters is performed in order to access the stability of the model. The paper concludes with conclusions and an outlook of possible future directions is depicted. [ABSTRACT FROM AUTHOR]

We study an expected payoff maximization problem for a risk-sensitive broker aiming to evaluate the merits of designing and underwriting an option contract on a traded commodity with geometric Brownian motion (GBM) spot price trajectories. Candidate firms for whom the contract would mitigate the commodity's price risk, each face Poisson demands that are currently the broker's responsibility to satisfy. Subject to a variance risk budget and a robustness requirement, the broker's objective is jointly to (1) choose a so-called trigger price function that will fundamentally define the option contract, and (2) select a value-maximizing set of client firms to whom the broker will offer the contract. We reformulate the problem as a bilevel program whose continuous relaxation we transform into a single-level, univariate problem with a convenient property that makes it amenable to line search methods. The optimal solution for that single-level problem is then raw material for constructing the optimal solution for the original problem. Our theoretical and experimental findings indicate that the contract's optimal value, and optimal trigger price function are both strictly monotone increasing in a cost parameter in the model, as well as in the GBM's volatility coefficient. The findings also show that those two quantities are strictly monotone decreasing in the GBM's drift coefficient. We conclude with a benchmarking sensitivity study which uses real-world data to study the implications of violating a certain constraint which implicitly bounds the optimal trigger price. [ABSTRACT FROM AUTHOR]

In this paper, we study an inventory system for products where demand depends on time and price. Shortages are allowed and are fully backordered. We suppose that the demand rate is the product of a power time pattern and a three-parametric exponential price function. The objective is to determine the economic lot size, the optimal shortage level and the best selling price to maximize the total profit per unit time. We present an efficient procedure to determine the optimal solution of the inventory problem for all possible scenarios. This procedure is illustrated with several numerical examples. A sensitivity analysis of the optimal inventory policy with respect to the parameters of the demand rate function is also given. Finally, the main contributions of this paper are highlighted and future research directions are introduced. [ABSTRACT FROM AUTHOR]

Directional distance function (DDF) has been a commonly used technique for estimating efficiency and productivity over the past two decades, and the directional vector is usually predetermined in the applications of DDF. The most critical issue of using DDF remains that how to appropriately project the inefficient decision-making unit onto the production frontier along with a justified direction. This paper provides a comprehensive literature review on the techniques for selecting directional vector of the directional distance function. It begins with a brief introduction of the existing methods around the inclusion of the exogenous direction techniques and the endogenous direction techniques. The former commonly includes arbitrary direction and conditional direction techniques, while the latter involves the techniques for seeking theoretically optimized directions (i.e., direction towards the closest benchmark or indicating the largest efficiency improvement potential) and market-oriented directions (i.e., directions towards cost minimization, profit maximization, or marginal profit maximization benchmarks). The main advantages and disadvantages of these techniques are summarized, and the limitations inherent in the exogenous direction-selecting techniques are discussed. It also analytically argues the mechanism of each endogenous direction technique. The literature review is end up with a numerical example of efficiency estimation for power plants, in which most of the reviewed directions for DDF are demonstrated and their evaluation performance are compared. [ABSTRACT FROM AUTHOR]

Regarding a two-echelon supply chain consisting of a logistics service integrator (LSI) and several functional logistics service providers (FLSPs), this paper establishes a two-stage order allocation model considering demand updating and the FLSPs’ fairness preferences. This model is a multi-objective programming model, whose goal is to maximize profits of the LSI and the total utility of FLSPs. The ideal point method is used to obtain the optimal solution. In the numerical example, the impacts of FLSPs’ behavioral parameters and demand update parameters on the order allocation in the social services network are discussed. Besides, multi-methodological method is used to verify the theoretical perspectives through an empirical study of Tianjin SND Logistics Company. Our study obtains a few important conclusions. For example, when demand of the second stage is updated, there is an optimal updating time maximizing the supply chain performance. Increased demand of the second stage results in greater supply chain performance. When the demand during the second stage decreases, the bigger the difference of the fairness preference coefficients among FLSPs, the greater the LSI’s profits and the lower the FLSPs’ total utility will be. However, the difference of the fairness preference coefficients among FLSPs has little influence on the LSI’s profits and total utility of the FLSPs, when the demand during the second stage increases. [ABSTRACT FROM AUTHOR]

In this paper we analyze the economic effects of implementing EPA's newly proposed regulations for carbon dioxide ( $$\hbox {CO}_2$$ ) on existing U.S. coal-fired power plants using nonparametric methods on a sample of 144 electricity generating units. Moreover, we develop an approach for evaluating the economic gains from averaging emission intensities among the utilities' generating units, compared to implementing unit-specific performance standards. Our results show that the implementation of flexible standards leads to up to 2.7 billion dollars larger profits compared to the uniform standards. Moreover, we find that by adopting best practices, current profits can be maintained even if an intensity standard of 0.88 tons of $$\hbox {CO}_2$$ per MWh is implemented. However, our results also indicate a trade-off between environmental and profit gains, since aggregate $$\hbox {CO}_2$$ emissions are higher with emission intensity averaging than with uniform standards. [ABSTRACT FROM AUTHOR]

We consider the facility location problem for an expanding chain which competes with other chains offering the same goods or service in a geographical area. Customers are supposed to select the facility with maximum utility to be served and facilities in the expanding chain may have different owners. We first use the weighted method to develop an integer linear programming model to obtain Pareto optimal locations related to the inner competition between the owners of the old facilities and the owners of the new facilities. This model is applied to maximizing the profit of the expanding chain taking into account the loss in market share of its old facilities caused by the entering of new facilities (cannibalization effect). A study with data of Spanish municipalities shows that the cannibalization effect can be significantly reduced by sacrificing a small portion of profit. [ABSTRACT FROM AUTHOR]

Traditionally, network design and line planning have been studied as two different phases in the planning process of public transportation. At the strategic level approaches dealing with the network design problem minimize travel time or maximize trip coverage, whereas at the tactical level, in the case of line planning, most models minimize cost or the number of transfers. The main novelty of this paper is the integration of the strategic and tactical phases of the rapid transit planning process. Specifically, a mathematical programming model that simultaneously determines the infrastructure network, line planning, train capacity of each line, fleet investment and personnel planning is defined. Moreover, the demand is assumed to be elastic and, therefore it is split into the rapid transit network and a competing mode according to a generalized cost. A rigorous analysis for the calibration of the different concepts that appear as consequence of the integration of phases is presented. Our approach maximizes the total profit of the network by achieving a balance between the maximum trip coverage and the minimum total cost associated to the network. Numerical results taking into account data based on real-world instances are presented. [ABSTRACT FROM AUTHOR]

The recirculating aquaculture system (RAS) is an intensive production line that uses recycled water, and that should operate continuously, year-round, at full capacity. The RAS depends on enhanced water quality and minimized fish stressors, and its profitability relies on maximizing economic productivity per unit volume of rearing space. However, RAS operation requires coordinated management of many unit processes and/or operations. The aim of this study was to optimize operating parameters, including the number of fingerlings in the system, their arrival frequency, and fish weight on entry into the system and into the various stages of sorting along the production line. It was also necessary to minimize the start-up period, i.e. the period between establishment and achievement of full design capacity. A simulation model was developed to further the operating company's interests, combining discrete-event and continuous-time stochastic simulations, meta-model and optimal-resource configurations-all to maximize annual profits, subject to operational and environmental constraints. Simulation outputs were monthly sales, fish stocking density (kilograms of biomass per cubic meter) and utilization of each culture tank at any given time, and effects of standing stock biomass and feed load on the biofilters. The simulation results were validated and implemented in an aquaculture farm. [ABSTRACT FROM AUTHOR]

The focus of this paper is on Dutch auctions where the bidding prices are restricted to a finite set of values and the number of bidders follows a Poisson distribution. The goal is to determine what the discrete bid levels should be to maximize the auctioneer’s expected revenue, which is the same as the average selling price of the object under consideration. We take a new approach to the problem by formulating the descending-price competitive bidding process as a nonlinear program. The optimal solution indicates that the interval between two successive bids should be wider as the Dutch auction progresses. Moreover, the auctioneer’s maximum expected revenue increases with the number of bid levels to be set as well as the expected number of bidders. Numerical examples are provided to illustrate the key results from this study and their managerial implications are discussed. [ABSTRACT FROM AUTHOR]

In this paper we empirically analyze several algorithms for solving a Huff-like competitive location and design model for profit maximization in the plane. In particular, an exact interval branch-and-bound method and a multistart heuristic already proposed in the literature are compared with uego ( Universal Evolutionary Global Optimizer), a recent evolutionary algorithm. Both the multistart heuristic and uego use a Weiszfeld-like algorithm as local search procedure. The computational study shows that uego is superior to the multistart heuristic, and that by properly fine-tuning its parameters it usually (in the computational study, always) find the global optimal solution, and this in much less time than the interval branch-and-bound method. Furthermore, uego can solve much larger problems than the interval method. [ABSTRACT FROM AUTHOR]

We develop optimal normative policies for pricing and advertising of products with limited availability by including the traditional product diffusion parameters (Bass, 1969)–innovation and imitation, and the scarcity effects generated due to limited product availability (Swami and Khairnar, 2003). Using optimal control methodology, our pricing policy results suggest that a profit-maximizing firm gradually increases the price as the sales approach the product availability. The optimal normative advertising policy recommends gradually decreasing the expenditure on the awareness advertising and increasing the expenditure on the availability advertising as the product diffusion progresses. These results are illustrated with suitable numerical examples. [ABSTRACT FROM AUTHOR]

Two new models for duopolistic competitive discrete location planning with sequential acting and variable delivered prices are introduced. If locations and prices are assumed to be set "once and for all" by the players, the resulting bilevel program is nonlinear. Under the assumption that further price adjustments are possible, i.e., that a Nash equilibrium in prices is reached, the model can be simplified to a linear discrete bilevel formulation. It is shown that in either situation players should not share any locations or markets if they strive for profit-maximization. For the situation with price adjustments, a heuristic solution procedure is suggested. In addition, the bilevel models are shown to serve as a basis from which different well-known location models -- as, for example, the p-median problem, the preemptive location problem and the maximum covering problem -- can be derived as special cases. [ABSTRACT FROM AUTHOR]

In this paper we discuss a locational model with a profit-maximizing objective. The model can be illustrated by the following situation. There is a set of potential customers in a given region. A firm enters the market and wants to sell a certain product to this set of customers. The location and demand of each potential customer are assumed to be known. In order to maximize its total profit, the firm has to decide: (1) where to locate its distribution warehouse to serve the customers; (2) the price for its product. Due to existence of competition, each customer holds a reservation price for the product. This reservation price is a decreasing function in the distance to the warehouse. If the actual price is higher than the reservation price, then the customer will turn to some other supplier and hence is lost from the firm's market. The problem of the firm is to find the best location for its warehouse and the best price for its product at the same time in order to maximize the total profit. We show that under certain assumptions on the complexity counts, a special case of this problem can be solved in polynomial time. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to modeling competition between firms in network-based industries, i.e. industries where the firms' technology decisions correspond to choices of networks. Industries having this structure include transportation, telecommunications, and some service industries. Competition is studied between two firms who make both network design decisions and price decisions for services. This situation is modeled as a game, an equilibrium solution corresponding to a Nash equilibrium is defined, and properties of the solution are characterized. Necessary and sufficient conditions are shown for equilibrium solutions and existence of equilibrium solutions is demonstrated. Among the results is that each Firm will maximize its own profit by minimizing total industry cost of providing services. An example demonstrating results is presented. [ABSTRACT FROM AUTHOR]