考虑路网可靠性和空间公平性的次优拥挤收费模型

根据随机路网环境下出行者规避风险的路径选择行为,提出了一种考虑路网可靠性和空间公平性的次优拥挤收费双层规划模型。其中,上层模型以具有空间公平性约束条件下最大化路网的社会福利为目标,下层模型是实施拥挤收费条件下考虑行程时间可靠性的弹性需求用户平衡模型。鉴于双层规划模型的复杂性,设计了基于遗传算法和FrankWolfe算法的组合式算法来求解提出的模型。算例结果表明:考虑行程时间可靠性的次优拥挤收费会产生不同于传统次优拥挤收费的平衡流量分布模式,表明出行者的路径选择行为对拥挤收费结果会产生直接影响;此外,算例结果还说明遗传算法对参数设置具有很强的鲁棒性。     

多方式弹性需求下公交定价双层规划模型

为描述多方式城市交通网络下公交定价与出行选择行为的相互作用与影响,将出行方式选择与路径选择涵盖于同一网络,建立了上层模型分别以企业利润最大化、乘客出行成本最小化和社会福利最大化为目标函数,下层模型为多方式弹性需求随机用户配流模型的公交定价双层规划模型。运用改进遗传算法对模型整体进行求解,下层模型采用综合对角化算法和MSA算法的组合求解算法。最后,设计了一个算例以说明模型应用。结果表明:运用双层规划模型所确定的公交票价较传统静态票价可使政府、企业及出行者三方都获得更高收益,且上层模型以社会福利最大化为目标函数能代表社会群体中多数人利益,优化效果最为理想。     

A heuristic for the multi-period petrol station replenishment problem

In the multi-period petrol station replenishment problem (MPSRP) the aim is to optimize the delivery of several petroleum products to a set of petrol stations over a given planning horizon. One must determine, for each day of the planning horizon, how much of each product should be delivered to each station, how to load these products into vehicle compartments, and how to plan vehicle routes. The objective is to maximize the total profit equal to the revenue, minus the sum of routing costs and of regular and overtime costs. This article describes a heuristic for the MPSRP. It contains a route construction and truck loading procedures, a route packing procedure, and two procedures enabling the anticipation or the postponement of deliveries. The heuristic was extensively tested on randomly generated data and compared to a previously published algorithm. Computational results confirm the efficiency of the proposed methodology.     

Optimal pricing for tandem queues with finite buffers

We consider optimal pricing for a two-station tandem queueing system with finite buffers, communication blocking, and price-sensitive customers whose arrivals form a homogeneous Poisson process. The service provider quotes prices to incoming customers using either a static or dynamic pricing scheme. There may also be a holding cost for each customer in the system. The objective is to maximize either the discounted profit over an infinite planning horizon or the long-run average profit of the provider. We show that there exists an optimal dynamic policy that exhibits a monotone structure, in which the quoted price is non-decreasing in the queue length at either station and is non-increasing if a customer moves from station 1 to 2, for both the discounted and long-run average problems under certain conditions on the holding costs. We then focus on the long-run average problem and show that the optimal static policy performs as well as the optimal dynamic policy when the buffer size at station 1 becomes large, there are no holding costs, and the arrival rate is either small or large. We learn from numerical results that for systems with small arrival rates and no holding cost, the optimal static policy produces a gain quite close to the optimal gain even when the buffer at station 1 is small. On the other hand, for systems with arrival rates that are not small, there are cases where the optimal dynamic policy performs much better than the optimal static policy.

     

Coordination between long-term decision process and day-ahead unit commitment in deregulated markets: A fuzzy hierarchical bi-level modeling approach

GenCos need the day-ahead unit commitment solutions in deregulated markets which are feasible, applicable in practice and consistent with the long-term planning decisions. However, such decisions are both vast in scope and different in nature so that applying a monolithic approach is subject to some difficulties and shortcomings. This paper aims to coordinate the long-term decision process with the day-ahead market scheduling through developing a profit-based fuzzy hierarchical bi-level approach. First, an annual planning model with monthly periods at power plant-generation technology level; then based upon a monthly scheduling with daily periods at generating unit level. An interactive solution method involving the soft coordination and feedback mechanisms using rolling horizon strategy is also presented. In the developed models, we try to address critical aspects of power system optimization. This approach is implemented for a real case and analytical results are reported.     

Scheduling ambulance crews for maximum coverage

This paper addresses the problem of scheduling ambulance crews in order to maximize the coverage throughout a planning horizon. The problem includes the subproblem of locating ambulances to maximize expected coverage with probabilistic response times, for which a tabu search algorithm is developed. The proposed tabu search algorithm is empirically shown to outperform previous approaches for this subproblem. Two integer programming models that use the output of the tabu search algorithm are constructed for the main problem. Computational experiments with real data are conducted. A comparison of the results of the models is presented.     

需求不确定的多周期的容量决策问题

研究每个周期的需求随机增加的情形下的容量扩充问题,建立起切合实际的有限周期随机动态规划模型及在期现值准则下的无限周期随机动态规划模型,进而探索生产单一产品的公司在面对随机增加的市场需求时,风险中立的管理者该如何扩充其生产容量,才能使得其公司在折扣意义下的总期望利润最大.研究无限阶段的容量扩充问题,得出某种约束条件下的优化策略解,给公司管理者提供了其长期可持续发展的优化策略和依据.     

Optimal Pricing and Production Planning for Multi-product Multi-period Systems with Backorders

In this paper, we develop models for production planning with coordinated dynamic pricing. The application that motivated this research is manufacturing pricing, where the products are non-perishable assets and can be stored to fulfill the future demands. We assume that the firm does not change the price list very frequently. However, the developed model and its solution strategy have the capability to handle the general case of manufacturing systems with frequent time-varying price lists. We consider a multi-product capacitated setting and introduce a demand-based model, where the demand is a function of the price. The key parts of the model are that the planning horizon is discrete-time multi-period, and backorders are allowed. As a result of this, the problem becomes a nonlinear programming problem with the nonlinearities in both the objective function and some constraints. We develop an algorithm which computes the optimal production and pricing policy on a finite time horizon. We illustrate the application of the algorithm through a detailed numerical example.     

A multi-period double coverage approach for locating the emergency medical service stations in Istanbul

We consider the multi-period location planning problem of emergency medical service (EMS) stations. Our objective is to maximize the total population serviced by two distinct stations within two different response time limits over a multi-period planning horizon. Our aim is to provide a backup station in case no ambulance is available in the closer station and to develop a strategic plan that spans multiple periods. In order to solve this problem, we propose a Tabu Search approach. We demonstrate the effectiveness of the proposed approach on randomly generated data. We also implement our approach to the case of Istanbul to determine the locations of EMS stations in the metropolitan area.     

Model and algorithms for multi-period sea cargo mix problem

In this paper, we consider the sea cargo mix problem in international ocean container shipping industry. We describe the characteristics of the cargo mix problem for the carrier in a multi-period planning horizon, and formulate it as a multi-dimensional multiple knapsack problem (MDMKP). In particular, the MDMKP is an optimization model that maximizes the total profit generated by all freight bookings accepted in a multi-period planning horizon subject to the limited shipping capacities. We propose two heuristic algorithms that can solve large scale problems with tens of thousands of decision variables in a short time. Finally, numerical experiments on a wide range of randomly generated problem instances are conducted to demonstrate the efficiency of the algorithms.     

考虑顾客退货和固定成本的联合补货与定价策略

为了吸引更多顾客,许多电子商务零售商允许顾客在一定时间内退货,导致其利润明显减少。同时,在补货时不仅产生依赖补货量的变动成本,而且会产生与补货量无关的固定成本。基于此,以最大化电子商务零售商的利润为目标,建立考虑顾客退货和固定成本的联合补货与定价模型,其中顾客的退货量与满足的需求呈正比。在一般需求情形下,部分刻画多期问题的最优策略;在特殊需求情形下,证明(s,S,p)策略对单期问题最优,并对多期问题的最优策略进行严格刻画。根据已有刻画为多期问题构造启发式策略。数值结果表明启发式策略近似最优;当初始库存水平足够高/低时,最优补货水平和定价随退货率与固定成本单调变化。关键词:联合补货与定价模型;顾客退货;固定成本;随机动态规划;最优策略     

Disassembly EOQ models with price-sensitive demands

The disassembly economic order quantity problem is to determine the quantities of a product to be disassembled at different times over an infinite planning horizon by considering ordering, operation, and inventory costs. The demands for the components are independent, which can lead to accumulations of unnecessary inventories over time. This article proposes the models which integrate price-sensitive demands and disposal decisions in disassembly economic order quantity problems to maximize the profit of disassembly systems without inventory accumulations. Three models are developed and analyzed to obtain solution approaches that give prices, the replenishment cycle time (or, equivalently, the order quantity), and the disposal quantity. The inventory policy integrating both pricing and disposal decisions allows higher profits to be achieved. A numerical experiment shows its efficiency and highlights its potential implementation in practical cases.     

Pricing,routing, and incentive compatibility in multiserver queues

This paper studies pricing and incentive issues in the assignment of customers to servers in a system that suffers congestion effects. When customers have private information about their waiting costs, a system administrator who wishes to maximize steady-sate net benefits per unit of time (i.e. total benefits from service minus total waiting costs) may do so using a pricing and routing scheme that is incentive compatible; that is, no customer has any incentive to reveal his private information untruthfully. When the system administrator wants to maximize toll revenue, the optimal scheme involves higher tolls, and hence lower congestion, than is socially optimal.     

Pricing and lot-sizing for a deteriorating item in a periodic review inventory system with shortages

We consider a single product that is, subject to continuous decay, a multivariate demand function of price and time, shortages allowed and completely backlogged in a periodic review inventory system in which the selling price is allowed to adjust upward or downward periodically. The objective of this paper is to determine the periodic selling price and lot-size over multiperiod planning horizon so that the total discount profit is maximized. The proposed model can be used as an add-in optimizer like an advanced planning system in an enterprise resource planning system that coordinates distinct functions within a firm. Particular attention is placed on investigating the effect of periodic pricing jointly with shortages on the total discount profit. The problem is formulated as a bivariate optimization model solved by dynamic programming techniques coupled with an iterative search process. An intensive numerical study shows that the periodic pricing is superior to the fixed pricing in profit maximization. It also clarifies that shortages strategy can be an effective cost control mechanism for managing deterioration inventory.     

Particle swarm optimization for bi-level pricing problems in supply chains

With rapid technological innovation and strong competition in hi-tech industries such as computer and communication organizations, the upstream component price and the downstream product cost usually decline significantly with time. As a result, an effective pricing supply chain model is very important. This paper first establishes two bi-level pricing models for pricing problems with the buyer and the vendor in a supply chain designated as the leader and the follower, respectively. A particle swarm optimization (PSO) based algorithm is developed to solve problems defined by these bi-level pricing models. Experiments illustrate that this PSO based algorithm can achieve a profit increase for buyers or vendors if they are treated as the leaders under some situations, compared with the existing methods.     

Electricity market near-equilibrium under locational marginal pricing and minimum profit conditions

This paper provides a tool to determine the near-equilibrium of an electric energy market. This market works under locational marginal pricing, i.e., generating units and demand loads are paid and pay, respectively, the locational marginal prices corresponding to the nodes they are connected to. The near-equilibrium is defined as the energy transaction levels for which generating companies maximize their respective profits and consumption companies maximize their respective utilities. An independent system operator clears the market maximizing the social welfare. Conditions that ensure minimum profit for generating units can be included. However, these conditions may render a generating unit uncompetitive and expel it from the market. Demands are taken to be non-constant and values are determined as part of the solution. The near-equilibrium is obtained through the solution of a mixed-integer quadratic problem equivalent to a mixed linear complementarity problem that includes the minimum profit conditions. It is important to note that the near-equilibrium concept presented in this paper does not solve a market equilibrium when indivisibilities such as start up costs or the like are present. Lastly, we validate the proposed model on a case study using data from the IEEE Reliability Test System.     

Optimal multi-period service capacity allocation and pricing allowing for uncertain competitive entry

A nonlinear programming model is formulated in this paper to determine the optimal scheme of capacity allocation and prices over a multi-period planning horizon for a service provider in the absence and presence of uncertain competitive entry. The model is solved for constant, decreasing, and increasing price sensitivities employing a combination of analytical and numerical methods. The study highlights the importance of advance selling of service prior to its eventual consumption in the spot period and investigates the impact of uncertain competitive entry on the optimal capacity allocation policy and its related profit if the entry is more or less likely or if the rival is more or less influential. The findings of the study reveal that the conclusions drawn from a two-period model are not necessarily generalizable to a model of a multi-period planning horizon.     

An integrated optimization model for managing the global value chain of a chemical commodities manufacturer

The realization of supply chain management concepts goes along with the introduction of comprehensive software systems for supporting decisions at the strategic, tactical, and operational planning level. Moreover, in industry the focus has shifted from a pure logistics-oriented view towards the integration of pricing and revenue issues into cross-functional value chain planning models. This paper presents a practical decision support tool for global value chain planning in the production of chemical commodities. The proposed linear optimization model consists of various modules that reflect sales, distribution, production, and procurement activities within a company-internal value chain. The objective of the model is to maximize profit by coordinating all activities within the supply chain. The model formulation is related to a real industry case. It is shown how the model can be used to support decision making from sales to procurement by volume and value.     

Customer selection problem with profit from a sideline

This paper deals with the problem of selecting profitable orders to accept out of customers sequentially arriving at companies operating in service industries which provide specialized services designed to meet the various needs of their customers. When all the orders accepted up to a point of time are completed and delivered, the companies provide subsidiary services as a sideline in order to prevent their system from being idle, and to yield extra income, referred to as the profit from a sideline. Further, a cost is paid to search for customers, called the search cost. We discuss the admission control problem and pricing control problem in an identical framework. Properties of the optimal decision rule maximizing the total expected present discounted net profit gained over an infinite planning horizon are examined and clarified. It is shown that when the profit from the sideline is large, the optimal policies may not be monotone in the number of orders in the system.     

Coordinating inventory control and pricing strategies: The continuous review model

We analyze an infinite horizon, single product, continuous review model in which pricing and inventory decisions are made simultaneously and ordering cost includes a fixed cost. We show that there exists a stationary (s,S) inventory policy maximizing the expected discounted or expected average profit under general conditions.