Volume flexible multi items inventory system with imprecise environment

This paper addresses a multi items volume flexible system for time dependent decaying items with the concept of machine breakdown and imprecise environment. In this study, partially backlogged shortages have been discussed. All the costs are fuzzified with signed distance method. Numerical examples are given to illustrate the theoretical results and sensitivity analysis is given to validate the results for various parameters

FUZZY INVENTORY MODEL FOR ITEMS WITH WEIBULL DISTRIBUTION DETERIORATION, POWER DEMAND, LINEAR HOLDING COST, SALVAGE COST AND PARTIAL BACKLOGGING

The objective of this research article is to develop an inventory model which incorporates power pattern demand, Weibull distribution deterioration, shortages and partial backlogging of orders. Holding cost is taken as time dependent and deteriorated items are assumed to have a salvage value. The cost parameters are fuzzified and the total cost is defuzzified using Graded mean representation, signed distance and centroid methods. The values obtained by these methods are compared with the help of numerical examples. The convexity of the cost function is depicted graphically. Sensitivity analysis is performed to study the effect of change in some parameters. Keywords: Inventory, Power demand, Partial backlogging, Deterioration, Triangular Fuzzy Number, Defuzzification, Graded mean represented method, Signed Distance Method, centroid method

Supply chain production model with preservation technology under fuzzy environment

In this paper, an attempt is made to characterize the preservation technology for deteriorating items to reduce the deterioration rate. This model assumes a single producer and single supplier and formulates a production model with a time varying rate of deterioration rate. Here production and demand are treated as a fuzzy variables and total cost is minimized for both the crisp and fuzzy model. Shortage is allowed on the supplier’s part, which is partially backlogged. A solution procedure is presented to determine an optimal replenishment cycle and total cost per unit time, which is a convex function of preservation technology cost. Results have been validated with relevant example. In a way, the proposed model provides a unique theory to reduce the deterioration rate for the production model

Inventory model with preservation technology and exponential holding cost in fuzzy scenario

Inventories are ubiquitous in the business sector. Since inventory is most frequently incurring expense, stock control is critical for an organization and it must be scrimping and saving in contemplation of function the merchandising fruitfully.  In this paper, an inventory model for a deteriorating item under exponential holding cost with collaborative preservation technology investment under carbon policy is considered.  Also, this study is developed in a fuzzy scenario by employing triangular fuzzy numbers.  Signed distance method is utilized to enhance decision making and optimization. Further the convexity of the total cost function for both the crisp and the fuzzy case is established.  The objective is to determine the optimal investment in preservation technology and the optimal cycle length so as to minimize the total cost. Moreover, some managerial results are obtained by using sensitivity analysis and graphical representation is also carried out.  The applications of the proposed model is used in the fields of constructing machinery or heavy duty construction equipment, specific chemicals and processed food

An integrated model for sustainable supplier selection and multi-period multi-product lot-sizing for packaging film industry in Iran

The emergence of sustainability issues has created increasing interest among those involved in the field of sustainable supply chain management. Companies are motivated to modify their supply chains activities based on sustainability issues to enhance their overall level of sustainability in order to fulfil demanding environmental and social legislation and to deal with increasing market forces from different stakeholder groups. Within supply chain activities, selecting appropriate suppliers based on the criteria of sustainability, e.g., economic, environmental, and societal might help companies move towards sustainable development. Although several studies have been accomplished to incorporate sustainability criteria into supplier selection problem, little attention has been paid to developing a comprehensive mathematical model that allocates the exact quantities of orders to suppliers considering lot-sizing problems. Moreover, the effect of inflation as an important issue for companies in the developing countries has been neglected in studies that examined multi-period multi-product lot-sizing along with supplier selection. In this study, a multi-objective mathematical model for sustainable supplier selection integrated with multi-period multi-product lot-sizing problem under the effects of inflation was developed. The model consists of four objective functions which are minimizing total cost, maximizing total social, total environmental score, and total economic qualitative scores. The mathematical model was developed based on the parameters discovered by preprocessing the social, environmental, and economic data of suppliers using a rule-based-weighted fuzzy approach and fuzzy analytical hierarchy process. The model attempted to simultaneously balance different costs under inflationary conditions to optimize the total cost of purchasing and other objective functions. A comprehensive framework was developed as a road map for procurement organizations in order to facilitate the allocation of optimal order quantities to suppliers in a sustainable supply chain. The proficiency and applicability of a proposed approach was illustrated using a case study of packaging films from the food industry. For each main criterion of sustainability, their related subcriteria and influencing factors were extracted from literature and the most related ones were selected by company’s experts. In this research, green competencies, environmental management system, pollution, occupational safety and health, training and education, contractual stakeholder, economic qualitative, and cost were selected by company’s experts as the main subcriteria of sustainable supplier selection. The consideration of sustainability criteria in the proposed multi-objective model revealed that a higher value of sustainable purchasing can be achieved in comparison with a single objective costbased model. In addition, the results show that the proposed model can provide a purchasing plan for the company while monitoring the effect of inflation and assuaging its concerns regarding sustainability issues

Integration of renewable energy sources: reliability-constrained power system planning and operations using computational intelligence

Renewable sources of energy such as wind turbine generators and solar panels have attracted much attention because they are environmentally friendly, do not consume fossil fuels, and can enhance a nation’s energy security. As a result, recently more significant amounts of renewable energy are being integrated into conventional power grids. The research reported in this dissertation primarily investigates the reliability-constrained planning and operations of electric power systems including renewable sources of energy by accounting for uncertainty. The major sources of uncertainty in these systems include equipment failures and stochastic variations in time-dependent power sources. Different energy sources have different characteristics in terms of cost, power dispatchability, and environmental impact. For instance, the intermittency of some renewable energy sources may compromise the system reliability when they are integrated into the traditional power grids. Thus, multiple issues should be considered in grid interconnection, including system cost, reliability, and pollutant emissions. Furthermore, due to the high complexity and high nonlinearity of such non-traditional power systems with multiple energy sources, computational intelligence based optimization methods are used to resolve several important and challenging problems in their operations and planning. Meanwhile, probabilistic methods are used for reliability evaluation in these reliability-constrained planning and design. The major problems studied in the dissertation include reliability evaluation of power systems with time-dependent energy sources, multi-objective design of hybrid generation systems, risk and cost tradeoff in economic dispatch with wind power penetration, optimal placement of distributed generators and protective devices in power distribution systems, and reliability-based estimation of wind power capacity credit. These case studies have demonstrated the viability and effectiveness of computational intelligence based methods in dealing with a set of important problems in this research arena

Assessing and Mitigating Risk in a Design for Supply Chain Problem

Industry leaders in today's global market strive for continuous improvement in order to remain competitive. One method used by firms for cutting costs and improving efficiency is Design for Supply Chain (DFSC). The objective of this methodology is to design the supply chain in parallel to designing or redesigning a new product. Risk is an inherent element of this DFSC process. Although supply chain risk models and new product development risk models are available, there are few models that consider the combined effect of risk to product development and the supply chain. A gap in the body of knowledge could be filled by a DFSC and risk model that looks at design, supply chain and risk concurrently. This research develops such a model and tests it on two data sets. The most critical risks to incorporate in the model were found through a review of the literature and a survey of industry experts. The model consists of two components. The first component is a Mixed Integer Programming (MIP) model which makes the DFSC decisions while simultaneously considering time-to-market risk, supplier reliability risk and strategic exposure risk. The results from the MIP are then used in the second model component which is a discrete event simulation. The simulation tests the robustness of the MIP solution for supplier capacity risk and demand risk. When a decision maker is potentially facing either of these risks the simulation shows whether it is best to use an alternative solution or proceed with the MIP solution. The model provides analytical results to be used by decision makers, but also allows decision makers to use their own judgment to select the best option for overall profitability. It is shown that the DFSC model with risk is a powerful decision making tool