Demand Variability And Supply Disruptions In Decentralized Retail Centres In A Supply Chain Network

The efficient management of the manufacturer–retail centre linkage in a supply chain network, is a multi-attribute decision making problem. It determines the market share and shapes the penetration of products into the market and retail centres. This demands that the customer strategic importance, cost, risk, e.t.c need to be harmonised. In this work a multi attribute decision model was used to determine the impacts of the retail centre risk in the form of demand variability or supply disruptions among other factors for a selected supply chain network that has eight retail centres.   The results of the demand variability of the eight retail centres are 1(0.44), 2(0.10), 3(0.88), 4(0.75), 5(0.56), 6(0.73), 7(0.25), 8(0.32), while the supply disruption are 1(0.35), 2(1.13), 3(1.13), 4(0.93), 5(0.93), 6(0.95), 7(0.35), 8(1.10) respectively. A sensitivity analysis of the decision criterion also showed the consequences of changes in the priority of the criteria and sub-criteria over the final decision. This helps the decision maker respond quickly and appropriately to changes in the fund management philosophy and competitive advantage position   Keywords: Decentralized retail centres, Demand variability and  Supply disruption

A Fuzzy-Analytical Hierarchy Model for Solid Waste Management Location in South-West Nigeria

Rapid urbanization and industrialization have led to the generation of considerable quantities of municipal and industrial wastes. These often result in spread of diseases, contaminations of water body and pollution of soil, thus the selection of a good landfill location is a multiple criteria problem. This work developed fuzzy analytical hierarchical model as a decision support system. The fuzzy based hierarchical model first converted the perception into triangular fuzzy numbers and used the concept of extent value analysis to obtain the significance of each of the criterion, sub criterion and the decision alternative. The developed model was applied to a landfill location problem of Ibadan, Oyo state. Five main criteria, sixteen sub criteria and three decision alternatives were considered via; Eleyele, Moniya and Iyana Ofa. The performances of Eleyele, Moniya, and Iyana Ofa through fuzzy based hierarchical model are 0.314, 0.324 and 0.385 respectively. The decision making technique indicates that, Iyana Ofa which has the highest performance should be selected for landfill location in Ibadan. Fuzzy analytic hierarchic process as a decision making technique is robust and can reduce imprecision in the mapping of perceptions of decision makers into numerical evaluation, thus making fuzzy based hierarchical model accurate, stable and reliable. Keywords: China insurance industry, Foreign fund, Challeng

Performance Evaluation of a Production Firm Using System Cycle Time Approach

Cycle time has become one of the most critical indicators in competitive manufacturing environments,  because it helps management focus on the two key factors in today’s marketplace – fully satisfying customer needs and conducting operations as cost efficiently as possible. In this era of build-to specifications, measuring cycle time and reducing non value-adding costs have become important managerial focal points. This study used the cycle time as a performance measure for a selected firm. The manufacturing process was described using a flowchart and a baseline for the critical activities which affect the cycle time for a batch production was established. After that, the activities were evaluated against the target to show current status. Factors which affect the times of these activities were also considered. The results show that on the average 30% of the manufacturing process did not meet with the time set for them and that each step in the process has a 45% chance of meeting its target time. This will reduce the average cycle time for a shift from 521 to 435 minutes, which is a 16.51% reduction. This work investigated the performance of manufacturing firm using cycle time approach. Keywords: Performance, cycle time, batch

A comparison of ARIMA and ANN techniques in predicting port productivity and berth effectiveness

Business process evaluation is a common norm in small-medium-large industries globally and information obtained during such evaluation have been used in simulating future performance of most industries using mathematical models such as Autoregressive Integrated Moving Average (ARIMA) and artificial neural network (ANN). This study explored the possibility of predicting port productivity and berth effectiveness of seaport using ANN and ARIMA. A comparative analysis of multi-layer perceptron (MLP) back propagation algorithm and ARIMA performance was carried out based on ships days at port, days at berth and tonnage which serves as model inputs, while port productivity and berth effectiveness were the model outputs. The MLP-ANN and ARIMA (1, 0, 4- port productivity) and (1, 0, 4-berth effectiveness) results were compared based on their coefficient of correlation and mean square error. The coefficient of correlation for port productivity prediction using MLP-ANN was 0.998. This value outperformed that of ARIMA (0.9862) for port productivity. The coefficient of correlation of 0.9956 and 0.9928 were obtained for berth effectiveness using MLR and ARIMA, respectively

DEVELOPMENT OF A MULTI-OBJECTIVE PRODUCTION PLANNING MODEL FOR A SAWMILL

Based on the objectives set out for a Sawmill, a goal programming model was developed to simultaneously consider the production volumes goal, sales revenue goal, production cost goal, and machine utilization goal in order to develop its production plans for a horizon. The unwanted deviations from the goals served as the objective function to be optimized subject to the goals constraints, operational constraints, and non-negativity constraints. Three independent pre-emptive goal priority structures, GP1, GP2, and GP3, were considered with each prioritizing the objectives differently. The goal programming model was tested for its utility using data gathered from the mill to the three-goal priority structures. The results obtained indicated that, for GP1, the product volume goals for all products were achieved, and all but one, volume goals were achieved for both GP2 and GP3. The viability test showed that all priority structures used were profitable with GP1, GP2, and GP3 recording 1.099, 1.102, and 1.095 respectively. This indicates that the three priority structures considered are approximately profitable at the same level. The goal programming model for production planning offers the decision-maker a variety of options as to its application

A framework for evaluating the performance of automated teller machine in banking industries: A queuing model-cum-TOPSIS approach

The improvement in the provision of banking services to customers enhances bank’s performance (profitability and productivity) and the amounts of dividend declared to shareholders as well as bank’s competitiveness. One means of fast tracking the service time for bank customers is through the use of self-servicing machines, such as automated teller machine (ATM). Total service cost, expected waiting time in queue, ATM utilization and percentage of customer loss are some of the performance indices that are used to evaluate the service rendered by a bank’s ATM. This study proposes a framework for evaluating the performance of ATM by integrating queuing model and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodology. Applicability of the framework was tested using practical data obtained from four banks in Nigeria. It was observed that the average ATM usage in the study area was less than 50%. The TOPSIS results identified Bank A as the best ranked bank. In addition, the results obtained revealed that banks with two ATM were ranked higher than banks with more than two AT