Search results

This article has been withdrawn as it was published elsewhere and accidentally duplicated. The original article can be seen here: 10.1108/eb014646. When citing the article, please cite: James H. Bookbinder, Timothy D. Locke, (1986), “Simulation Analysis of Just-in-Time Distribution”, International Journal of Physical Distribution & Materials Management, Vol. 17 Iss: 1, pp. 31 - 45.

A program of shipment consolidation (SCL) is the purposeful intervention by management to regularly combine several small shipments so that a larger load may be dispatched on the same vehicle. SCL decisions traditionally have been based upon minimization of total logistics costs (inventory plus transportation). The paper aims to answer the following research question: given the environmental implications of vehicle emissions as a function of load weight, are the familiar SCL policies still optimal?

Nonlinear expressions relating carbon dioxide (CO₂) emissions to vehicle weight, and parameterized by trip length and average travel speed, were derived from published experimental data. Those expressions were included in a simulation model that assessed the environmental impact, in addition to the logistics cost, of the policies concerning when to release a consolidated load.

For short holding times, the quantity policy performs best in terms of both logistics cost and pollution reduction. In the case of low‐order arrival rates and long holding times, the time policy is best at reducing emissions and logistics costs. However, the best dispatch policy conflicts in terms of pollution reduction and logistics cost minimization for the following cases: moderate holding times and long holding times combined with high‐order arrival rates. In these cases, it is necessary to consider the speed of travel, trip length and unit cost of emissions when evaluating the policies.

A carbon trading market appears to be on the horizon in several industries, which will establish a price per unit weight for CO₂ emissions and make it beneficial to minimize the total cost (including emissions) of the network. This research only considers CO₂ pollution, but future investigations could also consider other pollutants such as nitrogen oxides, carbon monoxide and volatile organic carbons.

SCL policies can include a “green logistics” component that is based on empirical data.

One undesirable consequence of transportation by truck is CO₂ emissions. However, the impact can be lessened, while still emphasizing total logistics cost per load, with our simulation‐based results for shipment release policies.

Two lot‐sizing heuristics are proposed for deterministic time‐varying demands, a case commonly encountered in requirements planning systems. The first heuristic simplifies the stopping rule of the Silver‐Meal (SM) heuristic so that difficult cases may be solved nearly optimally. The second combines the merits of both the SM and the Least‐Unit‐Cost heuristic Both perform favourably even when compared to recent modifications to the basic SM algorithm.

Presents a multiple‐objective mathematical programming model to co‐ordinate logistics decisions with those on the interface between the production and marketing departments. The model can help decide on an overall budget to request from senior management for logistics and these interfaces, and in systematically allocating the funds between transport, inventory and production. In so doing, this multi‐period model specifies the timing and quantity of raw‐material purchases, and the location and timing of production activities and distribution flows. The budget for expenditures on logistics and its interface activities is taken as an objective to minimise, instead of as a given dollar level to be satisfied. A second objective is to maximise the profit of logistics and its related interfaces. Trade‐offs between these two conflicting aims yields the decision maker′s “best compromise” solution.

Just‐in‐time (JIT) production has been a subject of considerable research in the past few years. The Japanese were the first to actually use JIT systems rather than the traditional economic order quantity inventory system or the more recent method of Material Requirements Planning (MRP). Considerable savings in inventory‐holding costs, faster spotting of defective producing stations and improved quality control have been observed using just‐in‐time production.

Today, many Canadian firms are seeking additional profits through sales to the European Community (EC). Successful market development in Europe will first require good contacts to obtain the best distribution channels. Access to the EC can hence be complicated through lack of knowledge of logistics systems in Europe and in particular countries. Secondly, vast numbers of rules, regulations and laws govern the exportation business. A firm can get bogged down simply from red tape. A European logistics information system could facilitate expansion to the EC. If properly designed and implemented, such a system could support a user in dealing with the two preceding issues. That system could furnish data on European logistics, and help especially with legal questions and paperwork. This article presents a conceptual model, and the general requirements and capabilities, of such a decision system to aid Canadian exports to Europe.

Decision analysis in management science employs concepts from economics such as utility functions and indifference curves. A utility function U models the “satisfaction” that a customer obtains from logistics service. Here U depends on two attributes (lead time, fill rate) whose values more directly represent customer service. The shipper can, at additional cost, improve either or both of these attributes. Constructs and maximizes various utility functions U given a total budget B for distribution service. Finds that without increasing the budget overall logistics service can often be improved from the customer’s point of view. Whether U is additive or multiplicative, a customer’s utility resulting from the optimal lead time and fill rate is typically 20 per cent higher than when those attribute levels are set intuitively (without reference to customer preferences and tradeoffs expressed by U). Gives some introduction to decision analysis (certainty equivalent, risk aversion, …) to aid in understanding the functional forms employed for U and methods of solution, rendering the paper more self‐contained.

Recently, 181 CEOs of notable corporations signed a joint statement at the Business Roundtable (2019) on the “Purpose of a Corporation” – declaring its aim as the creation of benefits for “all stakeholders.” This will likely accelerate the circular economy transition process. Harmonizing the interests of various stakeholders is essential for managing successful organizations and supply chains, which is similar to the first principle of using natural ecosystem thinking. According to that principle, it is essential to strike a balance between the producers, consumers, scavengers, and decomposers. We draw on stakeholder theory to identify various challenges and risks that restrict businesses from building sustainable circular systems. We turn our attention toward increasing the numbers of “scavengers” and “decomposers” in the system for attaining sustainable growth. Our emphasis is on (1) empowering organizational life cycle stages, (2) designing for “decomposability” and “scavengers,” and (3) suggesting the use of advanced optimization models for harmonizing stakeholder relationships.

This research compares the logistics systems of Asia and Europe and categorises them into distinct levels of logistics excellence. First, the context in Asia and in Europe is summarized. Then, attributes of a world‐class logistics system are proposed. By applying cluster analysis to data from authoritative sources, we objectively segregate European and Asian logistics systems into three logistics tiers. There are several surprises, the main one being that the UK is classified Tier 2 (not as favourable as Tier 1). A prioritized set of attributes that the UK could improve on to qualify for the Tier 1 group is suggested. Sensitivity analyses are conducted to determine changes to the classifications. After finding that the top‐ranking logistics systems of Europe and Asia are from Denmark and Singapore, respectively, those two countries are studied in detail to draw logistics lessons applicable elsewhere.