Setup Cost Reduction and Supply Chain Coordination in Case of Asymmetric Information

Screening contracts are a common approach to solve supply chain coordination problems under asymmetric information. Previous research in this area shows that asymmetric information leads to supply chain coordination deficits. We extend the standard framework of lotsizing decisions under asymmetric information by allowing investments in setup cost reduction. We find that asymmetric information leads to an overinvestment in setup cost reduction. Yet, the overall effect on supply chain performance is ambiguous. We show that these results holds for a wide variety of investment functions.

Quasi-Real Indexing-- The Pareto-Efficient Solution to Inflation Indexing

In a pure-exchange economy with one good, stochastic aggregate demand and supply, and consumers having the same relative-risk aversion, Pareto efficiency requires each individual’s consumption to be proportional to aggregate supply. While neither nominal contracts nor pure inflation- indexed contracts provide this proportionality, quasi-real contracts do. Quasi-real contracts adjust for aggregate-demand-caused inflation but not for aggregate-supply-caused inflation, causing their real obligations to be proportional to aggregate supply. When consumers differ in their relative risk aversion, or experience stochastic utility or endowment shocks, they will need insurance and other risk-transfer contracts in addition to quasi-real contracts.inflation indexing, quasi-real indexing

Manufacturing System Lean Improvement Design Using Discrete Event Simulation

Lean manufacturing (LM) has been used widely in the past for the continuous improvement of existing production systems. A Lean Assessment Tool (LAT) is used for assessing the overall performance of lean practices within a system, while a Discrete Event Simulation (DES) can be used for the optimization of such systems operations. Lean improvements are typically suggested after a LAT has been deployed, but validation of such improvements is rarely carried out. In the present article a methodology is presented that uses DES to model lean practices within a manufacturing system. Lean improvement scenarios are then be simulated and investigated prior to implementation, thereby enabling a systematic design of lean improvements

Performance modeling of e-procurement workflow using Generalised Stochastic Petri net (GSPN)

This paper proposes a Generalised Stochastic Petri net (GSPN) model representing a generic e-procurement workflow process. The model displays the dynamic behaviour of the system and shows the inter relationship of process activities. An analysis based on matrix equation approach enabled users to analyse the critical system's states, and thus justify the process performance. The results obtained allow users for better decision making in improving e-procurement workflow performance

A New Decision Support Framework for Managing Foot-and-mouth Disease Epidemics

Animal disease epidemics such as the foot-and-mouth disease (FMD) pose recurrent threat to countries with intensive livestock production. Efficient FMD control is crucial in limiting the damage of FMD epidemics and securing food production. Decision making in FMD control involves a hierarchy of decisions made at strategic, tactical, and operational levels. These decisions are interdependent and have to be made under uncertainty about future development of the epidemic. Addressing this decision problem, this paper presents a new decision-support framework based on multi-level hierarchic Markov processes (MLHMP). The MLHMP model simultaneously optimizes decisions at strategic, tactical, and operational levels, using Bayesian forecasting methods to model uncertainty and learning about the epidemic. As illustrated by the example, the framework is especially useful in contingency planning for future FMD epidemic

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

Integrated optimisation for production capacity, raw material ordering and production planning under time and quantity uncertainties based on two case studies

Abstract This paper develops a supply chain (SC) model by integrating raw material ordering and production planning, and production capacity decisions based upon two case studies in manufacturing firms. Multiple types of uncertainties are considered; including: time-related uncertainty (that exists in lead-time and delay) and quantity-related uncertainty (that exists in information and material flows). The SC model consists of several sub-models, which are first formulated mathematically. Simulation (simulation-based stochastic approximation) and genetic algorithm tools are then developed to evaluate several non-parameterised strategies and optimise two parameterised strategies. Experiments are conducted to contrast these strategies, quantify their relative performance, and illustrate the value of information and the impact of uncertainties. These case studies provide useful insights into understanding to what degree the integrated planning model including production capacity decisions could benefit economically in different scenarios, which types of data should be shared, and how these data could be utilised to achieve a better SC system. This study provides insights for small and middle-sized firm management to make better decisions regarding production capacity issues with respect to external uncertainty and/or disruptions; e.g. trade wars and pandemics.</jats:p

The Impact of Cheap Talk on Supply Chain Performance in Case of Asymmetric Information: An Experimental Investigation

The use of screening contracts is a common approach to solve supply chain coordination problems under asymmetric information. One major assumption in this context is that subjects will rather use their private information strategically than to reveal them truthfully, if they do not get any incentives to do this. This harms supply chain performance. This paper investigates the influence of costless pre-game communication (i.e. communication without any direct incentives) between a supplier and a buyer in a lotsizing framework. A laboratory experiment was conducted to test, whether this costless pre-game communication has (in contradiction to standard game-theory) an influence on supply chain coordination.experimental economics, screening contracts, supply chain coordination

Finished goods management for JIT production: new models for analysis

A firm is considered that manages its internal manufacturing operations according to a just-in-time system, but maintains an inventory of finished goods as a buffer against random demands from external customers. The finished goods inventory may be analysed by the methods of classical inventory theory in order to characterize the trade-off between inventory costs and schedule stability. A model is formulated in which the supply of finished goods is replenished by a small fixed quantity each time period. The size of the replenishment quantity may be revised only at pre-specified intervals. The single-interval problem is analysed, the cost-minimizing value of the replenishment quantity for a given revision interval length is computed, and the optimal cost is characterized as a function of the revision interval length. The dynamic problem is shown to be convex, with relatively easily computed optima. Finally, alternative formulations of the problem are described and suggestions made for further research