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

E-Fulfillment and Multi-Channel Distribution – A Review

This review addresses the specific supply chain management issues of Internet fulfillment in a multi-channel environment. It provides a systematic overview of managerial planning tasks and reviews corresponding quantitative models. In this way, we aim to enhance the understanding of multi-channel e-fulfillment and to identify gaps between relevant managerial issues and academic literature, thereby indicating directions for future research. One of the recurrent patterns in today’s e-commerce operations is the combination of ‘bricks-and-clicks’, the integration of e-fulfillment into a portfolio of multiple alternative distribution channels. From a supply chain management perspective, multi-channel distribution provides opportunities for serving different customer segments, creating synergies, and exploiting economies of scale. However, in order to successfully exploit these opportunities companies need to master novel challenges. In particular, the design of a multi-channel distribution system requires a constant trade-off between process integration and separation across multiple channels. In addition, sales and operations decisions are ever more tightly intertwined as delivery and after-sales services are becoming key components of the product offering.Distribution;E-fulfillment;Literature Review;Online Retailing

A Buffer Stocks Model for Stabilizing Price in Duopoly-Like Market

This paper presents the staple-food distribution problem in agro-industry. There is a great difference of staple-food supplies in the harvest-season and in the planting-season meanwhile the demand is relatively constant. This situation will trigger price-volatility and shortage of staple-food, and it causes opportunity-losses for the stakeholders (producer, consumer, wholesaler/trader, and the government). For stabilizing the price, the government has several stabilization policies; one of them is market-intervention policy by using buffer-stocks schemes. The market-intervention policy should be utilized for improving producer’s profit, for cutting consumer’s expenditure, and for sustaining wholesaler’s margin-profit by implementing price-support and price-stabilization. In duopoly-like market, we assume that there are only two market-players in the distribution system. The objective of this research is to determine the instruments for operating Market-Intervention Program which consist of the quantity, time, and price of the buffer-stocks schemes. The problem was solved using 3 approaches. First, a comparative cost/benefit analysis between free-market and intervention-market can be used to formulate the objective function of each stakeholders. Second, the integration of optimization model and econometrics model were use to develop the decision-variables subject to the expectation of stakeholders, the buffer-stocks requirement, and the dynamics price equilibrium properties. Third, model market with Inventory was applied for solving the market-price equilibrium. The result could be used to analyze such the staple-food distribution system, incorporating the configuration of duo-producers, duo market-buyers, and duo-consumers. Keywords: buffer-stocks, duopoly-like market, market-intervention program, model market with inventory, and staple-food distribution system

Global supply chains of high value low volume products

Imperial Users onl

Economic evaluation of bio-based supply chains with CO2 capture and utilisation

Carbon capture and storage (CCS) and carbon capture and utilisation (CCU) are acknowledged as important R&D priorities to achieve environmental goals set for next decades. This work studies biomass-based energy supply chains with CO2 capture and utilisation. The problem is formulated as a mixed-integer linear program. This study presents a flexible supply chain superstructure to answer issues on economic and environmental benefits achievable by integrating biomass-coal plants, CO2 capture and utilisation plants; i.e. location of intermediate steps, fraction of CO2 emissions captured per plant, CO2 utilisation plants' size, among others. Moreover, eventual incentives and environmental revenues will be discussed to make an economically feasible project. A large-size case study located in Spain will be presented to highlight the proposed approach. Two key scenarios are envisaged: (i) Biomass, capture or utilisation of CO2 are not contemplated; (ii) Biomass, capture and CO2 utilisation are all considered. Finally, concluding remarks are drawn.Peer ReviewedPostprint (author's final draft

Solving closed-loop supply chain problems using game theoretic particle swarm optimisation

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. In this paper, we propose a closed-loop supply chain network configuration model and a solution methodology that aim to address several research gaps in the literature. The proposed solution methodology employs a novel metaheuristic algorithm, along with the popular gradient descent search method, to aid location-allocation and pricing-inventory decisions in a two-stage process. In the first stage, we use an improved version of the particle swarm optimisation (PSO) algorithm, which we call improved PSO (IPSO), to solve the location-allocation problem (LAP). The IPSO algorithm is developed by introducing mutation to avoid premature convergence and embedding an evolutionary game-based procedure known as replicator dynamics to increase the rate of convergence. The results obtained through the application of IPSO are used as input in the second stage to solve the inventory-pricing problem. In this stage, we use the gradient descent search method to determine the selling price of new products and the buy-back price of returned products, as well as inventory cycle times for both product types. Numerical evaluations undertaken using problem instances of different scales confirm that the proposed IPSO algorithm performs better than the comparable traditional PSO, simulated annealing (SA) and genetic algorithm (GA) methods

The economic and environmental performance of distribution networks: A case study from the petrochemical industry

Designing a company's distribution network is a challenging task that requires the consideration of different aspects. In this respect, especially trade-offs between, for example, operational costs and customer service are the focus of the companies' attention. However, growing concerns of governments and customers about environmental protection have raised awareness towards the environmental impact of operations. Activities associated with the distribution of products, i.e. transportation and warehousing, are not yet subject to strict environmental regulations, but this situation is expected to change soon. Companies must, therefore, start to concentrate not only on economic but also on environmental aspects in the design of their supply chain. Based on a case study from the petrochemical industry, this paper presents a way to combine both, economic as well as environmental criteria, when evaluating (strategic) distribution network design decisions. The results show a trade-off between total (distribution) costs and transport carbon emissions. (author's abstract