Coordination of supply chains with bidirectional option contracts

In this paper we develop a supply contract for a two-echelon manufacturer–retailer supply chain with a bidirectional option, which may be exercised as either a call option or a put option. Under the bidirectional option contract, we derive closed-form expressions for the retailer’s optimal order strategies, including the initial order strategy and the option purchasing strategy, with a general demand distribution. We also analytically examine the feedback effects of the bidirectional option on the retailer’s initial order strategy. In addition, taking a chain-wide perspective, we explore how the bidirectional option contract should be set to attain supply chain coordination.     

An agent-based model of supply chains with dynamic structures

This paper proposes a common agent-based model for the simulation of MTS and MTO supply chains with dynamic structures. Based on the model, scholars can model supply chains easily. Basic characters of supply chains are proposed in the model. Agents, who are used to simulate the members of supply chains, produce appropriate products by intelligent choices. The relationships among agents are connected by their products. Different agents’ attributes are presented by their knowledge and actions of agents are introduced in the paper. Experiments are produced to show the availability of the agent-based model. The model should be available as a toolkit for the studying of dynamic supply chains.     

Coordination of supply chains by option contracts: A cooperative game theory approach

Manufacturer–retailer supply chains commonly adopt a wholesale price mechanism. This mechanism, however, has often led manufacturers and retailers to situations of conflicts of interest. For example, due to uncertain market demand, retailers prefer to order flexibly from manufacturers so as to avoid incurring inventory costs and to be able to respond flexibly to market changes. Manufacturers, on the other hand, prefer retailers to place full orders as early as possible so that they can hedge against the risks of over- and under-production. Such conflicts between retailers and manufacturers can result in an inefficient supply chain. Motivated by this problem, we take a cooperative game approach in this paper to consider the coordination issue in a manufacturer–retailer supply chain using option contracts. Using the wholesale price mechanism as a benchmark, we develop an option contract model. Our study demonstrates that, compared with the benchmark based on the wholesale price mechanism, option contracts can coordinate the supply chain and achieve Pareto-improvement. We also discuss scenarios in which option contracts are selected according to individual supply chain members’ risk preferences and negotiating powers.     

A flexible and generic approach to dynamic modelling of supply chains

In this paper, we present a new modelling approach for realistic supply chain simulation. The model provides an experimental environment for informed comparison between different supply chain policies. A basic simulation model for a generic node, from which a supply chain network can be built, has been developed using an object-oriented approach. This generic model allows the incorporation of the information and physical systems and decision-making policies used by each node. The object-oriented approach gives the flexibility in specifying the supply chain configuration and operation decisions, and policies. Stochastic simulations are achieved by applying Latin Supercube Sampling to the uncertain variables in descending order of importance, which reduces the number of simulations required. We also present a case study to show that the model is applicable to a real-life situation for dynamic stochastic studies.     

Production lot-sizing with dynamic capacity adjustment

In this paper we study a single-item lot-sizing model in which production capacity can be adjusted from time to time. There are a number of different production capacity levels available to be acquired in each period, where each capacity level is assumed to be a multiple of a base capacity unit. To reduce the waste of excess of capacity but guarantee meeting the demand, it is important to decide which level of capacity should be acquired and how many units of the item should be produced for every period in the planning horizon. Capacity adjustment cost incurs when capacity acquired in the current period differs from the one acquired in the previous period. Capacity acquisition costs, capacity adjustment costs, and production costs in each period are all time-varying and depend on the capacity level acquired in that period. Backlogging is allowed. Both production costs and inventory costs are assumed to be general concave. We provide optimal properties and develop an efficient exact algorithm for the general model. For the special cases with zero capacity adjustment costs or fixed-plus-linear production costs, we present a faster exact algorithm. Computational experiments show that our algorithm is able to solve medium-size instances for the general model in a few seconds, and that cost can be reduced significantly through flexible capacity adjustment.     

Integrated pricing and lot-sizing decisions in a serial supply chain

In this article, we consider a serial supply chain controlled by a decision-maker who is responsible for deciding the amount of raw material to order from the selected suppliers, the amount of product to transfer between consecutive stages in order to avoid any inventory shortages, and the final product's selling price so that the profit per time unit is maximized. Coordinating all these decisions simultaneously is a topic that has been neglected in literature. This integrated process is modeled as a mixed-integer nonlinear programming model. In addition, the model requires the order quantity received from each selected supplier to be an integer multiple of the order quantity delivered to the following stage, which means that a different multiplicative factor can be assigned to each supplier. This coordination mechanism shows an improvement in the objective function compared to existing models that assign the same multiplicative factor to each selected supplier. Moreover, we develop a heuristic algorithm that generates near optimal solutions in a timely manner. Two numerical examples are presented to illustrate the proposed model and the heuristic algorithm.     

A dynamic uncapacitated lot-sizing problem with co-production

We consider an extension of the dynamic uncapacitated lot-sizing problem to account for co-production, where multiple products are produced simultaneously in a single production run. We formulate the problem as a mixed-integer linear programming problem. We then show that a variant of the well-known zero-inventory property holds for this problem, and use this property to extend a dynamic program given for the single-item lot-sizing to solve the problem with co-production. Finally, we provide an illustrative example for our approach.     

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.     

Cost analysis in global supply chains

This paper aims to explore effect of supply chain members’ costs change on participants of the network. On one perspective, it explores when there is a cost change to a firm, how other firms are affected and who bear(s) the most effect. On the other perspective, it investigates how an individual firm’s performance is affected by the other members in its network and whose cost change would impose a most significant effect on its profit.     

Measurement and optimization of robust stability of multiclass queueing networks: Applications in dynamic supply chains

Multiclass queueing networks are an essential tool for modeling and analyzing complex supply chains. Roughly speaking, stability of these networks implies that the total number of customers/jobs in the network remains bounded over time. In this context robustness characterizes the ability of a multiclass queueing network to remain stable, if the expected values of the interarrival and service times distributions are subject to uncertain shifts. A powerful starting point for the stability analysis of multiclass queueing networks is the associated fluid network. Based on the fluid network analysis we present a measure to quantify the robustness, which is indicated by a single number. This number will be called the stability radius. It represents the magnitude of the smallest shift of the expected value of the interarrival and/or service times distributions so that the associated fluid network looses the property of stability. The stability radius is a worst case measure and is a conceptual adaptation from the dynamical systems literature. Moreover, we provide a characterization of the shifts that destabilize the network. Based on these results, we formulate a mathematical program that minimizes the required network capacity, while ensuring a desired level of robustness towards shifts of the expected values of the interarrival times distributions. This approach provides a new view on long-term robust production capacity allocation in supply chains. The capabilities of our method are demonstrated using a real world supply chain.     

Managing raw material in supply chains

In this paper, we explore how firms can manage their raw material sourcing better by developing appropriate sourcing relationships with their raw material suppliers. We detail three empirical case studies of firms explaining their different raw material sourcing strategies: (a) firms can adopt a hands-off approach to raw material management, (b) firms can supply raw material directly to their suppliers, and this may be beneficial for some agents in the supply chain, and (c) firms can bring their component suppliers together, and the resulting cooperation between suppliers can be beneficial for supply chain. We then analytically model the three raw material scenarios encountered in our empirical work, examine the resulting profits along the supply chain, and extend the results to a competitive buyer scenario. Overall, our results show that active management of raw material sourcing can add value to supply chains.     

Profit allocation games in supply chains

The paper considers a supply chain where a number of agents are connected in some network relationship. Game theory is a very powerful framework for studying decision making problems, involving a group of agents in a supply chain. Allocation games examine the allocation of value among agents connected by a network. The ongoing actions in the supply chain are a mix of cooperative and non-cooperative behavior of the participants. The paper proposes a two-stage procedure for profit allocation based on combination of non-cooperative and cooperative game approaches. In the first stage, retailers meet customer price-dependent stochastic demand and seek to maximize total profit from the sale. Retailers are trying to align goals with producers on a contract basis and share the total profit with them. In the second stage, the cooperating producers allocate individual profits.     

The coordinated replenishment dynamic lot-sizing problem with quantity discounts

In the classical coordinated replenishment dynamic lot-sizing problem, the primary motivation for coordination is in the presence of the major and minor setup costs. In this paper, a separate element of coordination made possible by the offer of quantity discounts is considered. A mathematical programming formulation for the extended problem under the all-units discount price structure and the incremental discount price structure is provided. Then, using variable redefinitions, tighter formulations are presented in order to obtain tight lower bounds for reasonable size problems. More significantly, as the problem is NP-hard, we present an effective polynomial time heuristic procedure, for the incremental discount version of the problem, that is capable of solving reasonably large size problems. Computational results for the heuristic procedure are reported in the paper.     

Preferences for contractual forms in supply chains

The supply chain contracting literature has focused on incentive contracts designed to align supply chain members’ individual interests. A key finding of this literature is that members’ preferences for contractual forms are often at odds: the upstream supplier prefers relatively complex contracts that can coordinate the supply chain; however, the downstream retailer prefers a wholesale price-only contract because it leaves more surplus (than does a coordinating contract), which the retailer can capture. This paper addresses the following question: Under what circumstances do suppliers and retailers prefer the same contractual form? We study supply chain members’ preferences for contractual forms under three different competitive settings in which multiple supply chains compete to sell substitutable products in the same market. Our analysis suggests that both upstream and downstream sides of the supply chain may prefer the same “quantity discount” contract, which would eliminate the conflicts of interest that otherwise typify contracting situations. More interesting still is that both sides may also prefer the wholesale price-only contract; this finding provides a theoretical explanation for why that inefficient (but simple) contract is widely adopted in supply chain transactions.     

Bargaining in competing supply chains with uncertainty

Substantial literature has been devoted to supply chain coordination. The majority of this literature ignores competition between supply chains. Moreover, a significant part of this literature focuses on coordination that induce the supply chain members to follow strategies that produce the equilibria chosen by a vertically integrated supply chain. This paper investigates the equilibrium behavior of two competing supply chains in the presence of demand uncertainty. We consider joint pricing and quantity decisions and competition under three possible supply chain strategies: Vertical Integration (VI), Manufacturer’s Stackelberg (MS), and Bargaining on the Wholesale price (BW(α), α is the bargaining parameter) over a single or infinitely many periods. We show that, in contrast to earlier literature, using VIVI (VI in both chains) is the unique Nash Equilibrium over one period decision, while using MSMS or BW(α)BW(α) may be Nash Equilibrium over infinitely many periods.     

Capacitated dynamic lot-sizing problem with delivery/production time windows

In this paper we generalize the classical dynamic lot-sizing problem by considering production capacity constraints as well as delivery and/or production time windows. Utilizing an untraditional decomposition principle, we develop a polynomial-time algorithm for computing an optimal solution for the problem under the assumption of non-speculative costs. The proposed solution methodology is based on a dynamic programming algorithm that runs in O(nT⁴) time, where n is the number of demands and T is the length of the planning horizon.     

Planning for demand failure: A dynamic lot size model for clinical trial supply chains

This paper examines the optimal production lot size decisions for clinical trial supply chains. One unique aspect of clinical trial supply chains is the risk of failure, meaning that the investigational drug is proven unsafe or ineffective during human testing and the trial is halted. Upon failure, any unused inventory is essentially wasted and needs to be destroyed. To avoid waste, manufacturers could produce small lot sizes. However, high production setup costs lead manufacturers to opt for large lot sizes and few setups. To optimally balance this tradeoff of waste and destruction versus production inefficiency, this paper generalizes the Wagner-Whitin model (W-W model) to incorporate the risk of failure. We show that this stochastic model, referred to as the failure-risk model, is equivalent to the deterministic W-W model if one adjusts the cost parameters properly to reflect failure and destruction costs. We find that increasing failure rates lead to reduced lot sizes and that properly incorporating the risk of failure into clinical trial drug production can lead to substantial cost savings as compared to the W-W model without the properly adjusted parameters.     

Order-Up-To policies in Information Exchange supply chains

Collaboration in Supply Chains (SC) is concerned with the alignment of the decision making process amongst SC partners. This is crucial in the planning and inventory management area where this alignment is enabled by the exchange of information. Several benefits deriving from such effective collaboration exist, such as: excess inventory elimination, lead times reduction, improved customer service, efficient product development, etc. Operations Management literature proclaims the virtues of collaboration and information sharing but academicians and practitioners have recently identified various gaps that still need further work. More specifically it has been shown that several deleterious phenomena as the bullwhip effect; inventory instability and intermittent orders are not completely eliminated in Information Exchange supply chains. The reason is mainly because companies adopt order policies that are prone to create instability along the SC. In this paper we show how the performance of an Information Exchange SC can be improved by shifting from a myopic periodic review Order-Up-To policy to a periodic review Order-Up-To with feedback gain. To do so, we model the SC structure through difference equations and study the system response in term of internal process efficiency and customer service level.     

Benefits of working capital sharing in supply chains

Supply chain finance and working capital management are important avenues to reduce supply chain costs. Small suppliers may not have sufficient working capital to finance their operations and efficiently supply their customers. We develop a model that captures the fundamental aspects of financial and operational planning in a two-stage supply chain, with both strong and weak members. A strong member can negotiate for more favorable financing rates, more advantageous payment terms, and shorter lead times than a weaker member. We investigate two working capital allocation scenarios. In the dedicated working capital allocation scenario, the members of the supply chain each have their own working capital. In the joint working capital allocation scenario, the members of the supply chain have a joint pool of working capital. Our results demonstrate significant benefits when the members of the supply chain share the working capital. We also show that extending payment delays to a supplier upstream results in higher overall supply chain costs.