An optimal two-level supply chain model for Small- and Medium-sized Enterprises (SMEs) considering rework for new products and price-dependent demands

With the advent of new technologies, several factors such as globalization of markets, customers' different needs, and increasingly fierce economic competition have encouraged Small- and Medium-sized Enterprises (SMEs) to improve their engagement with suppliers and to involve themselves with cost management practices in order to survive. SMEs clearly need to focus on the interests of the entire supply chain by enacting win-win policies. In this regard, the present study investigated a two-level inventory model featuring a manufacturer and a buyer in the competitive market with the policy of producing new products. The proposed model took into account imperfect and low-quality products and their capacities for rework. In other words, due to the competitive nature of the market, any increase in prices would lead to a decrease in demand. The mathematical model was proposed in two scenarios: one with the possibility of shortage and one without it. The objective function of the mathematical model revolves around maximizing the total profit of the supply chain considering both independent and joint optimization by the supply chain members. A new algorithm was then proposed to solve the mathematical model whose applicability was evaluated by using a numerical example in the analysis software MATLAB as the input. The results were then analyzed and discussed based on a sensitivity analysis approach

An investigation of production and transportation policies for multi-item and multi-stage production systems

Die vorliegende kumulative Dissertation besteht aus fünf Artikeln, einem Arbeitspapier und vier Artikeln, die in wissenschaftlichen Zeitschriften veröffentlicht wurden. Alle fünf Artikel beschäftigen sich mit der Losgrößenplanung, jedoch mit unterschiedlichen Schwerpunkten. Artikel 1 bis 4 untersuchen das Economic Lot Scheduling Problem (ELSP), während sich der fünfte Artikel mit einer Variante des Joint Economic Lot Size (JELS) Problems beschäftigt. Die Struktur dieser Dissertation trägt diesen beiden Forschungsrichtungen Rechnung und ordnet die ersten vier Artikel dem Teil A und den fünften Artikel dem Teil B zu

The lot sizing problem: A tertiary study

This paper provides a survey of literature reviews in the area of lot sizing. Its intention is to show which streams of research emerged from Harris' seminal lot size model, and which major achievements have been accomplished in the respective areas. We first develop the methodology of this review and then descriptively analyze the sample. Subsequently, a content-related classification scheme for lot sizing models is developed, and the reviews contained in our sample are discussed in light of this classification scheme. Our analysis shows that various extensions of Harris' lot size model were developed over the years, such as lot sizing models that include multi-stage inventory systems, incentives, or productivity issues. The aims of our tertiary study are the following: firstly, it helps primary researchers to position their own work in the literature, to reproduce the development of different types of lot sizing problems, and to find starting points if they intend to work in a new research direction. Secondly, the study identifies several topics that offer opportunities for future secondary research

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