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

Warehousing and Inventory Management in Dual Channel and Global Supply Chains

More firms are adopting the dual-channel supply chain business model where firms offer their products to customers using dual-channel sales (to offer the item to customers online and offline). The development periods of innovative products have been shortened, especially for high-tech companies, which leads to products with short life cycles. This means that companies need to put their new products on the market as soon as possible. The dual-channel supply chain is a perfect tool to increase the customer’s awareness of new products and to keep customers’ loyalty; firms can offer new products online to the customer faster compared to the traditional retail sales channel. The emergence of dual-channel firms was mainly driven by the expansion in internet use and the advances in information and manufacturing technologies. No existing research has examined inventory strategies, warehouse structure, operations, and capacity in a dual-channel context. Additionally, firms are in need to integrate their global suppliers base; where the lower parts costs compensate for the much higher procurement and cross-border costs; in their supply chain operations. The most common method used to integrate the global supplier base is the use of cross-dock, also known as Third Party Logistic (3PL). This study is motivated by real-world problem, no existing research has considered the optimization of cross-dock operations in terms of dock assignment, storage locations, inventory strategies, and lead time uncertainty in the context of a cross-docking system. In this dissertation, we first study the dual-channel warehouse in the dual-channel supply chain. One of the challenges in running the dual-channel warehouse is how to organize the warehouse and manage inventory to fulfill both online and offline (retailer) orders, where the orders from different channels have different features. A model for a dual-channel warehouse in a dual-channel supply chain is proposed, and a solution approach is developed in the case of deterministic and stochastic lead times. Ending up with numerical examples to highlight the model’s validity and its usefulness as a decision support tool. Second, we extend the first problem to include the global supplier and the cross-border time. The impact of global suppliers and the effect of the cross-border time on the dual-channel warehouse are studied. A cross-border dual-channel warehouse model in a dual-channel supply chain context is proposed. In addition to demand and lead time uncertainty, the cross-border time is included as stochastic parameter. Numerical results and managerial insights are also presented for this problem. Third, motivated by a real-world cross-dock problem, we perform a study at one of the big 3 automotive companies in the USA. The company faces the challenges of optimizing their operations and managing the items in the 3PL when introducing new products. Thus, we investigate a dock assignment problem that considers the dock capacity and storage space and a cross-dock layout. We propose an integrated model to combine the cross-dock assignment problem with cross-dock layout problem so that cross-dock operations can be coordinated effectively. In addition to lead time uncertainty, the cross-border time is included as stochastic parameter. Real case study and numerical results and managerial insights are also presented for this problem highlighting the cross-border effect. Solution methodologies, managerial insights, numerical analysis as well as conclusions and potential future study topics are also provided in this dissertation

Managing Warehouse Utilization: An Analysis of Key Warehouse Resources

The warehousing industry is extremely important to businesses and the economy as a whole, and while there is a great deal of literature exploring individual operations within warehouses, such as warehouse layout and design, order picking, etc., there is very little literature exploring warehouse operations from a systems approach. This study uses the Theory of Constraints (TOC) to develop a focused resource management approach to increasing warehouse capacity and throughput, and thus overall warehouse performance, in an environment of limited warehouse resources. While TOC was originally developed for reducing operational bottlenecks in manufacturing, it has allowed companies in other industries, such as banking, health care, and the military, to save millions of dollars. However, the use of TOC has been limited to case studies and individual situations, which typically are not generalizable. Since the basic steps of TOC are iterative in nature and were not designed for survey research, modifications to the original theory are necessary in order to provide insight into industry-wide problems. This study further develops TOC\u27s logistics paradigm and modifies it for use with survey data, which was collected from a sample of warehouse managers. Additionally, it provides a process for identifying potentially constrained key warehouse resources, which served as a foundation of this study. The findings of the study confirm that TOC\u27s methods of focused resource capacity management and goods flow scheduling coordination with supply chain partners can be an important approach for warehouse managers to use in overcoming resource capacity constraints to increase warehouse performance

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

Improving warehouse responsiveness by job priority management: a European distribution centre field study

Warehouses employ order cut-off times to ensure sufficient time for fulfilment. To satisfy increasing consumer’s expectations for higher order responsiveness, warehouses competitively postpone these cut-off times upholding the same pick-up time. This paper, therefore, aims to schedule jobs more efficiently to meet compressed response times. Secondly, this paper provides a data-driven decision-making methodology to guarantee the right implementation by the practitioners. Priority-based job scheduling using flow-shop models has been used mainly for manufacturing systems but can be ingeniously applied for warehouse job scheduling to accommodate tighter cut-off times. To assist warehouse managers in decision making for the practical value of these models, this study presents a computer simulation approach to decide which priority rule performs best under which circumstances. The application of stochastic simulation models for uncertain real-life operational environments contributes to the previous literature on deterministic models for theoretical environments. The performance of each rule is evaluated in terms of a joint cost criterion that integrates the objectives of low earliness, low tardiness, low labour idleness, and low work-in-process stocks. The simulation outcomes provide several findings about the strategic views for improving responsiveness. In particular, the critical ratio rule using the real-time queue status of jobs has the fastest flow-time and performs best for warehouse scenarios with expensive products and high labour costs. The case study limits the coverage of the findings, but it still closes the existent gap regarding data-driven decision-making methodology for practitioners of supply chains

E-logistics of agribusiness organisations

Logistics is one of the most important agribusiness functions due to the idiosyncrasy of food products and the structure of food supply chain. Companies in the food sector typically operate with poor production forecasting, inefficient inventory management, lack of coordination with supply partners. Further, markets are characterised by stern competition, increasing consumer demands and stringent regulation for food quality and safety. Large agribusiness corporations have already turned to e-logistics solutions as a means to sustain competitive advantage and meet consumer demands. There are four types of e-logistics applications: (a) Vertical alliances where supply partners forge long-term strategic alliances based on electronic sharing of critical logistics information such as sales forecasts and inventory volume. Vertical alliances often apply supply chain management (SCM) which is concerned with the relationship between a company and its suppliers and customers. The prime characteristic of SCM is interorganizational coordination: agribusiness companies working jointly with their customers and suppliers to integrate activities along the supply chain to effectively supply food products to customers. E-logistics solutions engender the systematic integration among supply partners by allowing more efficient and automatic information flow. (b) e-tailing, in which retailers give consumers the ability to order food such as groceries from home electronically i.e. using the Internet and the subsequent delivery of those ordered goods at home. (c) Efficient Foodservice Response (EFR), which is a strategy designed to enable foodservice industry to achieve profitable growth by looking at ways to save money for each level of the supply chain by eliminating inefficient practices. EFR provides solutions to common logistics problems, such as transactional inefficiency, inefficient plant scheduling, out-of-stocks, and expedited transportation. (d) Contracting, a means of coordinating procurement of food, beverages and their associated supplies. Many markets and supply chains in agriculture are buyer-driven where the buyers in the market tend to set prices and terms of trade. Those terms can include the use of electronic means of communication to support automatic replenishment of goods, management of supply and inventory. The results of the current applications of e-logistics in food sector are encouraging for Greek agribusiness. Companies need to become aware of and evaluate the value-added by those applications which are a sustainable competitive advantage, optimisation of supply chain flows, and meeting consumer demands and food safety regulations. E-business diffusion has shown that typically first-movers gain a significant competitive advantage and the rest companies either eventually adopt the new systems or see a significant decline in their trading partners and perish. E-logistics solutions typically require huge investments in hardware and software and skilled personnel, which is an overt barrier for most Greek companies. Large companies typically are first-movers but small and medium enterprises (SMEs) need institutional support in order to become aware that e-logistics systems can be fruitful for them as well

Augmenting the distribution of goods from warehouses in dynamic demand environments using intelligent agents

Warehouses are being impacted by increasing e-commerce and omni-channel commerce. Future innovation may predominantly involve automation but many warehouses remain manually operated. The golden rule of material handling is smooth product flow, but there are day-to-day operational issues that occur in the warehouse that can impact this and order fulfilment. Standard operational process is paramount to warehouse operational control but inflexible processes don’t allow for a dynamic response to real-time operational constraints. The growth of IoT sensor and data analytics technology provide new opportunities for designing warehouse management systems that detect and reorganise around real-time constraints to mitigate the impact of day-to-day warehouse operational issues. This paper presents an intelligent agent framework for basic warehouse management systems that is distributed, is structured around operational constraints and includes the human operator at operational and decision support levels. An agent based simulation was built to demonstrate the viability of the framework