“It is remarkable that an industry that is built around the management of process and materials flows in plants has been slow to grasp the principle of organizational processes and logistics flows. But based on the success of such methods in other sectors, this is the future; …” – Braithwaite, 2002. This clearly indicates the state of the chemical industry in paying attention to supply chain logistics. Logistics is the glue that binds the entities of a supply chain (Karimi et al., 2005). According to the Council of Logistics Management (Lambert, 2001), “Logistics is that part of the supply chain process that plans, implements, and controls the efficient, effective flow and storage of goods, services, and related information from the point-of-origin to the point-of-consumption in order to meet customer requirements”.

The definition of logistics – “the flow of material, information, and money between consumers and suppliers” (Frazelle, 2002) emphasizes the link between logistics performance and customer satisfaction. Today, logistics is much more than transportation alone; it includes many other services. Lieb and Randall (1996) showed that the most frequently outsourced logistics services are warehouse management/operations, shipment consolidation, carrier selection, logistics information systems, rate negotiation, and fleet management/operations with the significant expansion of services including product assembly/installation, product returns, and customer spare parts.

Whether it is a chemical company that manages its own logistics, or a third party logistics provider (3PL) that manages it for the chemical company, the ultimate cost of logistics directly affects the cost effectiveness of global chemical supply chains (Jetlund et al., 2004). According to Karimi et al. (2002), “Often an overlooked component of the chemical business, a critical examination of logistics practices can result in substantial savings”. While logistics is an issue of increasing importance to almost all industries, it is of most relevance to the chemical industry, as various types of chemical and related industries have some of the highest logistics costs. Logistics costs can vary from 3.6% of the purchase price for a best-in-class (BIC) site to 20% at the other extreme (Karimi et al., 2002).

Logistics costs in the chemical and related industries are among the highest in asset-intensive supply chains. Having managed the intra-plant logistics well for years, the companies are now looking for ways to lower the costs of enterprise-wide logistics by increasingly outsourcing a variety of logistics services to third-party logistics (3PL) firms globally. We present a systematic and quantitative decision-making formalism to address the integrated logistics needs of a MNC in a global business environment. Although our goal is to address the logistics in chemicals and related industries in particular, the methodology is general and applicable to other supply chains as well. The formalism involves a novel representation of logistics activities in terms of a recipe superstructure and a static MILP model based on that to select the optimal contracts (or/and in-house execution) that minimize the total logistics cost. The contracts are designed to fulfill partial or full bundles of various logistics needs, tasks, and services, which can be performed at globally distributed sites. We account for product bundling and transport expenses between various sites in bulk or packaged or container forms and to various customers. Our goal is to identify the contracts (hence the providers) and the location of each service, which serve the total needs of a company in an integrated and most cost-effective manner.

We address this problem from the perspective of a chemical company who signs one/multiple contracts with logistics companies. We first develop a powerful framework for representing this complex problem in a comprehensive and general manner, and then use that to develop a multi-period mixed integer linear programming (MILP) formulation. We use several examples to highlight the advantages of the proposed approach. It allows the flexibility of selecting partial contracts, which reduces the combinatorial complexity and computation time considerably, along with some reduction in costs under certain assumptions. The model not only accommodates existing contracts, but also allows new contracts to extend beyond the horizon. Thus, it is able to address in a reactive manner the various dynamic disruptions that normally arise in chemical supply chains. We also found that the full selection of contracts are not only costly, it is also computationally expensive. The CPU time is much larger in the case of full selection of contracts.

Key words: Logistics; 3PLs; contracts; supply chain; chemical

Braithwaite, A. Achieving world class supply chain and logistics in the chemical industry. EPCA Logistics Meeting Monaco, November 2002.

Karimi, I.A., Sharafali, M., Mahalingam, H. Scheduling tank container movements for chemical logistics. AICHE, 2005, 51, 178-197.

Lambert, D.M. The Supply Chain Management and Logistics Controversy. In: Brewer, A.M., Button, K.J., Hensher, D.A., (Eds.), Handbook of Logistics and Supply-Chain Management. Pergamon Publishers, Netherland, pp 99 – 126, 2001.

Frazelle, E. Supply chain strategy: the logistics of supply chain management, New York, McGraw Hill Pub Co, 2002.

Lieb, R., and Randall, H. A comparison of the use of third party logistics services by large American manufacturers, 1991, 1994, and 1995. Journal of Business Logistics, 1996, 17(1), pp 305-320.

Jetlund, A.S., Karimi, I.A. Improving the logistics of multi-compartment chemical tankers. Computers & Chemical Engineering, 2004, 28, 1267-1283.

Karimi, I.A., Srinivasan, R., Han, P.L. Unlock supply chain improvements through effective logistics. Chemical Engineering Progress, 2002, 5, 32-38.