Pharmaceutical supply chain networks with outsourcing under price and quality competition

In this paper, we present a pharmaceutical supply chain network model with outsourcing under price and quality competition, in both equilibrium and dynamic versions. We consider a pharmaceutical firm that is engaged in determining the optimal pharmaceutical flows associated with its supply chain network activities in the form of manufacturing and distribution. In addition to multimarket demand satisfaction, the pharmaceutical firm seeks to minimize its total cost, with the associated function also capturing the firm's weighted disrepute cost caused by possible quality issues associated with the contractors. Simultaneously, the contractors, who compete with one another noncooperatively in prices in the manner of Bertrand, and in quality, seek to secure manufacturing and distribution of the pharmaceutical product from the pharmaceutical firm. This game theory model allows for the determination of the optimal pharmaceutical product flows associated with the supply chain in‐house and outsourcing network activities and provides the pharmaceutical firm with its optimal make‐or‐buy decisions and the optimal contractor selections. We state the governing equilibrium conditions and derive the equivalent variational inequality formulation. We then propose dynamic adjustment processes for the evolution of the product flows, the quality levels, and the prices, along with stability analysis results. The algorithm yields a discretization of the continuous‐time adjustment processes. We present convergence results and compute solutions to numerical examples to illustrate the generality and applicability of the framework.     

Modelling inter-supply chain competition with resource limitation and demand disruption

This paper proposes a comprehensive model for studying supply chain versus supply chain competition with resource limitation and demand disruption. We assume that there are supply chains with heterogeneous supply network structures that compete at multiple demand markets. Each supply chain is comprised of internal and external firms. The internal firms are coordinated in production and distribution and share some common but limited resources within the supply chain, whereas the external firms are independent and do not share the internal resources. The supply chain managers strive to develop optimal strategies in terms of production level and resource allocation in maximising their profit while facing competition at the end market. The Cournot–Nash equilibrium of this inter-supply chain competition is formulated as a variational inequality problem. We further study the case when there is demand disruption in the plan-execution phase. In such a case, the managers need to revise their planned strategy in order to maximise their profit with the new demand under disruption and minimise the cost of change. We present a bi-criteria decision-making model for supply chain managers and develop the optimal conditions in equilibrium, which again can be formulated by another variational inequality problem. Numerical examples are presented for illustrative purpose.     

The effect of firm number on equilibrium product positioning and pricing: a marketing–production perspective

We examine how product design and pricing are affected when the number of firms in the market increases by considering marketing and production variables. We employ a model that adopts marketing notions such as market shares and ideal points to dictate the attraction of the product to consumers. The model also incorporates production costs where the cost of the product increases linearly with increasing product attribute levels. The modeling framework facilitates the existence of a Nash equilibrium in prices and product positions. The number of firms in the market is exogenously defined. When the number of firms in the market increases, firms lower their prices and design their product with features closer to the market's ideal point. This results in lower profits.     

Multi‐product supply chain horizontal network integration: models,theory, and computational results

In this paper, we develop multi‐product supply chain network models with explicit capacities, before and after their horizontal integration. In addition, we propose a measure, which allows one to quantify and assess, from a supply chain network perspective, the synergy benefits associated with the integration of multi‐product firms through mergers/acquisitions. We utilize a system‐optimization perspective for the model development and provide the variational inequality formulations, which are then utilized to propose a computational procedure which fully exploits the underlying network structure. We illustrate the theoretical and computational framework with numerical examples. This paper is a contribution to the literatures of supply chain integration and mergers and acquisitions.     

The generalized set-valued strongly nonlinear implicit variational inequalities

In this paper, we introduce and study a new class of generalized set-valued strongly nonlinear implicit variational inequalities in Hilbert spaces. We construct the algorithm for solving this kind of generalized set-valued strongly nonlinear implicit variational inequality problem by using the auxiliary principle technique of Glowinski, Lions, and Tremolieres, prove the existence of solutions for this class of generalized set-valued strongly nonlinear implicit variational inequalities and the convergence of iterative sequences generated by the algorithm.     

A Fully Distributed Hybrid Control Framework For Non-Differentiable Multi-Agent Optimization

This paper develops a fully distributed hybrid control framework for distributed constrained optimization problems. The individual cost functions are non-differentiable and convex. Based on hybrid dynamical systems, we present a distributed state-dependent hybrid design to improve the transient performance of distributed primal-dual first-order optimization methods. The proposed framework consists of a distributed constrained continuous-time mapping in the form of a differential inclusion and a distributed discrete-time mapping triggered by the satisfaction of local jump set. With the semistability theory of hybrid dynamical systems, the paper proves that the hybrid control algorithm converges to one optimal solution instead of oscillating among different solutions. Numerical simulations illustrate better transient performance of the proposed hybrid algorithm compared with the results of the existing continuous-time algorithms.      

How to go global with differentiated products

This paper employs a three-stage game to analyze the entry preference for foreign firms and host country with product differentiation. We derive a theoretical support of entry decision for multinational enterprises. It finds that lower product differentiation induces higher (lower) technology transfer given a sufficiently low (high) technology transfer cost. Moreover, the foreign firm prefers acquisition given sufficiently low transfer costs just like entering developed countries. However, probability for the equilibrium mode of acquisition to induce higher technology (than direct entry) decreases in product differentiation. We also find that both the government and the foreign firm prefer identical entry mode only when technology transfer cost is at a certain low level. Probability of this identical situation generally decreases in product differentiation. Contrarily, the governments in relatively highly developing countries generally welcome acquisition mode while the foreign firms prefer direct entry.     

A GIS-Based Optimization Framework for Competitive Multi-Facility Location-Routing Problem

In a dynamic market setting, firms need to quickly respond to shifting demographics and economic conditions. In this paper, we investigate the problem of determining the optimum set of locations for a firm, which operates a chain of facilities under competition. We consider the objective of maximizing profit, defined as gross profit margin minus logistics costs. We propose a location-routing model where revenue is realized according to probabilistic patronization of customers and routing costs are incurred due to vehicles serving the open facilities from a central depot. We propose a hybrid heuristic optimization methodology for solving this model. The optimal locations are searched for by a Genetic Algorithm while an integrated Tabu Search algorithm is employed for solving the underlying vehicle routing problem. The solution approach is tested on a real dataset of a supermarket chain. The results show that the location decisions made by the proposed methodology lead to increased market share and profit margin, while keeping logistics costs virtually unchanged. Finally, we present a GIS-based framework that can be used to store, analyze and visualize all data as well as model solutions in geographic format.     

A variational inequality approach for marketable pollution permits

In this paper, we present a variational inequality framework for the modeling, qualitative analysis, and computation of equilibria in markets in pollution permits. The models developed herein allow for different modes of competitive behavior, including oligopolistic behavior, while taking into account the cost of polluting plus the prices of the licenses to pollute at different receptor points. The models deal explicitly with spatial differentiation and also ensure that the imposed environmental quality standards are met through the initial allocation of licenses. An algorithm is proposed, along with convergence results, to compute the profit-maximized quantities of the firms' products and quantities of emissions, as well as the equilibrium allocation of licenses and their prices. Numerical examples are included to illustrate the approach. This is the first time that this methodology is utilized in environmental economics.     

制造系统的递阶滚动优化调度模型

研究的对象是只有一台不可靠（failure-prone)机器的非完全柔性制造系统，该系统能生产多种产品，但在同一时刻只能生产一种产品，并且当机器由生产一种产品向生产另一种产品切换时，需要考虑setup时间及其成本，待决策变量是setup序列及产品生产率，本文基于非完全柔性制造系统的特点，引入递阶层控的思想，采用新的递阶结构框架和阈值控制策略，对问题进行分解，建立了考虑setup时间及成本的递阶流率控制最优化调度模型，并给出了递阶的滚动优化算法，仿真结果表明，这种调度策略更易于工程实现。     

一个关于求解k-种产品选址问题的近似算法

对于k-种产品工厂选址问题,有如下描述：存在一组客户和一组可以建立工厂的厂址。现在有k种不同的产品,要求每一个客户必须由k个不同的工厂来提供k种不同的产品,其中每个工厂都只能为客户提供唯一的一种产品。在该问题中,假定建厂费用以及任意两个结点之间的运输费用都为非负,并且任意两个结点之间的运输费用都满足对称和三角不等式关系的性质。问题的要求是要从若干厂址中选择一组厂址来建立工厂,给每个工厂指定一种需要生产的产品,并且给每一个客户提供一组指派使每个客户都能有k个工厂来为其供应这k种不同的产品。对于此类问题,优化目标是最小化建厂费用以及运输费用。论文在假设建厂费用为零的前提下,提出了求解该类问题的一种最坏性能比为3k/2-1的近似算法。     

Surpetitive strategy as a portfolio for the next millennium

Due to the gloom of global economics, competition among manufacturing firms is getting even tougher. Lean production, agile manufacturing, total quality management, and World‐Class philosophies are not providing robust solutions that enable those companies to face such a turbulent environment. This ongoing research work proposes a framework that consists of a set of strategies that enable companies not only to maintain their market share but also to go beyond. It also focuses on speeding‐up time to market as a key driver for business competitiveness. © 2000 John Wiley & Sons, Inc.     

服务差异化背景下基于行为的定价策略

在竞争企业具有服务差异化的背景下,研究一种定价歧视策略-----基于行为的定价(behavior-based pricing,BBP).采用博弈论方法构建两周期动态定价模型,通过价格和利润的对比分析进一步探讨服务水平差异化企业最优定价策略,最后分析BBP与服务差异化的交互作用.主要研究结论如下:1)服务差异化程度和相对服务成本两大因素交互影响着企业的最优定价策略.具体地,服务差异化程度较低(高)且相对服务成本较小(大)时,竞争企业均不采用(采用)BBP;服务差异化程度较低(高)但服务提升成本较大(小)时,竞争企业存在混合战略纳什均衡,双方有一定概率采用BBP.2)混合战略纳什均衡情形下,BBP导致的激烈价格竞争并不总是损害竞争双方的利润.当服务差异化程度较低且服务提升成本较大时,高服务水平企业反而能在这种价格竞争中实现利润增加.3)当服务差异化程度较高且相对服务成本较大时,BBP与服务差异化的交互作用能够实现服务差异化企业利润的帕累托改进,实现双赢的局面.     

信息不对称条件下寡头集团转移定价决策分析

研究信息不对称条件下存在中间产品外部市场的寡头集团转移定价决策问题.在不完全竞争中间产品外部市场条件下,当集团之间信息不对称时,对中间产品内外部实行单一定价,转移价格将大于中间产品的边际成本;对中间产品内外部实行差别定价时,转移价格则等于中间产品的边际成本.通过对两种策略的比较可知,寡头集团实行差别定价还是单一定价,取决于中间产品外部市场和最终产品市场的需求价格弹性.     

Single-machine scheduling with advanced process control constraints

With increasing worldwide competition, high technology manufacturing companies have to take great care to lower their production costs and guarantee high quality at the same time. Advanced process control (APC) is widely used in semiconductor manufacturing to adjust machine parameters so as to achieve satisfactory product quality. When there is a conflict between quality and scheduling objectives, quality usually takes precedence. This paper studies the interaction between scheduling and APC. A single-machine multiple-job-types makespan problem with APC constraints is proved to be NP-hard. For some special cases, optimal solutions are obtained analytically. In more general cases, the structure of optimal solutions is explored. An efficient heuristic algorithm based on these structural results is proposed and compared to an integer programming approach.     

Improving the Solution of Variational Inequalities Based on the Optimization Approach

An optimization approach to solving a convex finite-dimensional variational inequality with nonpotential operator is examined. It is shown how to construct an optimization problem equivalent to the variational inequality in the space of the original variables. A first-order algorithm to solve variational inequalitieis is formulated based on this optimization problem.     

Platform technologies and network goods: insights on product launch and management

Entrepreneurs of technology platforms and network goods face distinctive challenges in managing customer adoption, and in trading off growth and profitability. The firm has several levers of control including managing product design and the intensity of network effects, managing the timing of product announcement versus actual product release, selecting the target market for initial product launch, and whether to sell a single version or an expanded product line. Product line expansion is especially useful under network effects. A freemium approach can help the firm manage both growth (via the free product) and profitability (via the premium higher-priced version). However, expanding the product line carries substantial fixed costs (e.g., marketing cost, cost of additional plant, managing multiple sets of inventory, increased distribution cost). Firms are deterred from incurring these fixed costs when there is uncertainty about product success. Such uncertainty is particularly relevant for multi-sided networks—where the value from joining one network (e.g., users) depends on the size of the other side (e.g., developers)—because potential participants on each side may be uncertain about participation on the other side. Despite uncertainty, product line expansion can be attractive for both startups and established firms. Established firms face lower uncertainty about developer participation, and should expand when fixed costs of expansion are low (and do so early in the product’s life cycle). In contrast, startup firms face greater uncertainty in securing participation from third-party developers, and are more likely to benefit from a “wait and see” or deferred expansion strategy.     

Distributed cooperative industrial demand response

Industrial demand response, whereby energy-intensive industrial processes shift their production to take advantage of time-varying electricity prices, is a popular topic of recent research. In a traditional demand response problem, the industrial process will have customers which set their own schedule for purchases of the industrial product, which the industrial process must meet. However, by introducing cooperation between an industrial process and its customers, additional cost savings are possible. In this work, we present an optimization framework for cooperative demand response, whereby the industrial process provides economic incentives to customers to shift their schedules to better align with the utility costs seen by the industrial process. As the industrial process and its customers are likely to be different entities which do not share their operational models, we propose a distributed algorithm for solving the problem using the alternate direction method of multipliers, which enables solving the problem with minimal information sharing. The ability of this algorithm to obtain solutions which improve upon the status quo is showcased through multiple case studies. We further demonstrate that cooperation provides the most benefit when the industrial process has limited ability to store its product and when the customer has a high degree of flexibility. We also show that this idea is practically applicable through a case study where an industrial process supplies hydrogen and nitrogen to an ammonia producer.     

Competitive equilibrium in e-commerce: Pricing and outsourcing

The success of firms engaged in e-commerce depends on their ability to understand and exploit the dynamics of the market. One component of this is the ability to extract maximum profit and minimize costs in the face of the harsh competition that the internet provides. We present a general framework for modeling the competitive equilibrium across two firms, or across a firm and the market as a whole. Within this framework, we study pricing choices and analyze the decision to outsource IT capability. Our framework is novel in that it allows for any number of distributions on usage levels, price–QoS tradeoffs, and price and cost structures.     

Scheduling one-part-type serial manufacturing system under periodic demand: a solvable case

The paper studies one-part type, multiple-stage production system with periodic demands. A buffer of infinite capacity is placed after each machine. Inventory flow through buffers is controlled by machine production rates. The objective is to find a cyclic production rate, which minimizes all inventory-related expenses over an infinite planning horizon. With the aid of the maximum principle, optimal production policies are derived and the continuous-time scheduling problem is reduced to a discrete timing problem. As a result, a polynomial-time algorithm is suggested to calculate the optimal production rate. A numerical example is used to illustrate the algorithm.Scope and purposeNumerical and heuristic approaches have been suggested for production control of automated-serial-manufacturing systems. These approaches try to derive production control policies that would minimize overall costs related to inventory, backlog, and production. The quality of these approaches is often difficult to assess, and they can be time-consuming to implement. Therefore, increasing attention has been directed to optimal control policies of production systems that can be derived precisely and quickly. This paper addresses a special case of the production system manufacturing a single product type to meet a periodic demand. Given a certain assumption on cost relationship, we derive a fast and simple scheduling algorithm that calculates the optimal policy.