Search results

Introduction Operations research, i.e. the application of scientific methodology to operational problems in the search for improved understanding and control, can be said to have started with the application of mathematical tools to military problems of supply bombing and strategy, during the Second World War. Post‐war these tools were applied to business problems, particularly production scheduling, inventory control and physical distribution because of the acute shortages of goods and the numerical aspects of these problems.

This paper seeks to identify and assess the problems of distribution and logistics that arise in the fishery sector in Greece and to examine the impact of market orientation with regard to these problems.

The paper is based on the findings of a survey involving 186 companies. Descriptive statistics for each variable were used in order to assess the importance of each problem of distribution and logistics. Cluster analysis was carried out based on the perception of the importance of the problems of distribution and logistics. In addition, “crosstabs”analysis was used to examine the association between distribution problems and the firm characteristics of each cluster. Finally, linear multiple regression analysis was carried out, with each problem of distribution and logistics taken as the dependent variable and each element of marketing and logistics taken as an independent variable.

The importance of distribution and logistics problems varied widely, as did the market orientation between the groups of participating firms. In addition, certain firm characteristics and infrastructure factors can become so significant that they directly affect the degree of importance of the above problems.

Distribution & Logistics Managers should be aware of the significant influence that certain characteristics of the firms can have on the distribution function. Special attention should be paid to the importance of the distribution problems and the role of market orientation.

Unlike earlier research carried out in this domain, this study deals with a much wider range of problems and a broader cross‐section of companies. In addition, it is the first to focus in detail on the degree of importance of distribution problems and the role of market orientation.

The distribution sector has been hard hit by the energy/ecology crisis. Higher fuel costs coupled with reduced availability of many energy sources have adversely affected distribution activities. Growing levels of pollution have caused global concern. As a part of the physical distribution activity, the transportation modes have been particularly vulnerable to the energy/ecology crisis because they rely so heavily on energy resources. It is important that those involved in physical distribution understand the distribution‐energy/ecology interface. Recognition of the effects that the energy/ecology crisis has had, and will have, on distribution is an integral part of logistics planning and control. The energy/ecology crisis will not go away and it behoves the physical distribution manager, educator and public policy maker to: (1) Understand the Problem, (2) Recognise how the problem pertains to him directly and/or indirectly, and (3) Determine how he and others will react to the problem in the future.

To achieve a full understanding of the role of marketing from plan to profit requires a knowledge of the basic building blocks. This textbook introduces the key concepts in the art or science of marketing to practising managers. Understanding your customers and consumers, the 4 Ps (Product, Place, Price and Promotion) provides the basic tools for effective marketing. Deploying your resources and informing your managerial decision making is dealt with in Unit VII introducing marketing intelligence, competition, budgeting and organisational issues. The logical conclusion of this effort is achieving sales and the particular techniques involved are explored in the final section.

In the last four years, since Volume I of this Bibliography first appeared, there has been an explosion of literature in all the main functional areas of business. This wealth of material poses problems for the researcher in management studies — and, of course, for the librarian: uncovering what has been written in any one area is not an easy task. This volume aims to help the librarian and the researcher overcome some of the immediate problems of identification of material. It is an annotated bibliography of management, drawing on the wide variety of literature produced by MCB University Press. Over the last four years, MCB University Press has produced an extensive range of books and serial publications covering most of the established and many of the developing areas of management. This volume, in conjunction with Volume I, provides a guide to all the material published so far.

Preface The functions of business divide into several areas and the general focus of this book is on one of the most important although least understood of these—DISTRIBUTION. The particular focus is on reviewing current practice in distribution costing and on attempting to push the frontiers back a little by suggesting some new approaches to overcome previously defined shortcomings.

The purpose of this paper is to present results concerning resource distribution problems for a class of production systems composed of production operations described by relations with uncertain parameters – for newly considered serial‐parallel and parallel‐serial structures.

The resource distribution problems are formulated. For the typical mathematical model of a single production operation, the resource distribution algorithms are derived analytically or, when that is impossible, numerical procedures for finding solutions to distribution problems are suggested.

The uncertain variables have been proved as a convenient tool for solving specific optimization problems in production management based on relational knowledge representation with unknown parameters.

The paper presents analytical resource distribution and numerical algorithms for determining the optimal resource distribution, which may be applied in knowledge‐based management‐level decision systems for serial‐parallel and parallel‐serial structures of production systems.

Key components of the logistics mix are described in an effort to create an understanding of the total logistics concept. Chapters include an introduction to logistics; the strategic role of logistics, customer service levels, channel relationships, facilities location, transport, inventory management, materials handling, interface with production, purchasing and materials management, estimating demand, order processing, systems performance, leadership and team building, business resource management.

This study aims to minimize the transportation-related cost in distribution while utilizing a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach. An increased cost in distribution is a major problem for many companies due to the absence of efficient planning methods to overcome operational challenges in distinct distribution networks. The problem addressed in this study is to minimize the transportation-related cost in distribution while using a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach which has not gained the adequate attention in the literature.

This study formulated the transportation problem as a vehicle routing problem with a heterogeneous fixed fleet and workload balancing, which is a combinatorial optimization problem of the NP-hard category. The model was solved using both the simulated annealing and a genetic algorithm (GA) adopting distinct local search operators. A greedy approach has been used in generating an initial solution for both algorithms. The paired t-test has been used in selecting the best algorithm. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet compositions of the heterogeneous fleet. Results were analyzed using analysis of variance (ANOVA) and Hsu’s MCB methods to identify the best scenario.

The solutions generated by both algorithms were subjected to the t-test, and the results revealed that the GA outperformed in solution quality in planning a heterogeneous fleet for distribution with load balancing. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet utilization with different compositions of the heterogeneous fleet. Results were analyzed using ANOVA and Hsu’s MCB method and found that removing the lowest capacities trucks enhances the average vehicle utilization with reduced travel distance.

The developed model has considered both planning of heterogeneous fleet and the requirement of work load balancing which are very common industry needs, however, have not been addressed adequately either individually or collectively in the literature. The adopted solution methodologies to solve the NP-hard distribution problem consist of metaheuristics, statistical analysis and scenario analysis are another significant contribution. The planning of distribution operations not only addresses operational-level decision, through a scenario analysis, but also strategic-level decision has also been considered.

The planning of distribution operations not only addresses operational-level decisions, but also strategic-level decisions conducting a scenario analysis.

Distribution problems deal with distribution from a number of sources to a number of destinations. Each source offers amounts of goods, while each destination demands quantities of these goods. The object is to find the cheapest transporting schedule that satisfies demand without violating supply restraints. In this paper we propose the use of fuzzy sets to represent the provisional information related to costs, demands and other variables. Moreover, we suggest including the problem of shortest route for the distribution vehicles. Finally, to solve this complex problem we propose using a genetic algorithm with a fuzzy fitness function.