An economic lot and delivery scheduling problem with the fuzzy shelf life in a flexible job shop with unrelated parallel machines

This paper considers an economic lot and delivery scheduling problem (ELDSP) in a fuzzy environment with the fuzzy shelf life for each product. This problem is formulated in a flexible job shop with unrelated parallel machines, when the planning horizon is finite and it determines lot sizing, scheduling and sequencing, simultaneously. The proposed model of this paper is based on the basic period (BP) approach. In this paper, a mixed-integer nonlinear programming (MINLP) model is presented and then it is changed into two models in the fuzzy shelf life. The main model is dependent to the multiple basic periods and it is difficult to solve the resulted proposed model for large-scale problems in reasonable amount of time; thus, an efficient heuristic method is proposed to solve the problem. The performance of the proposed model is demonstrated using some numerical examples

Extensions to the dynamic requirements planning model

"April 1998."Includes bibliographical references (p. 32).by John Ruark

Modeling Industrial Lot Sizing Problems: A Review

In this paper we give an overview of recent developments in the field of modeling single-level dynamic lot sizing problems. The focus of this paper is on the modeling various industrial extensions and not on the solution approaches. The timeliness of such a review stems from the growing industry need to solve more realistic and comprehensive production planning problems. First, several different basic lot sizing problems are defined. Many extensions of these problems have been proposed and the research basically expands in two opposite directions. The first line of research focuses on modeling the operational aspects in more detail. The discussion is organized around five aspects: the set ups, the characteristics of the production process, the inventory, demand side and rolling horizon. The second direction is towards more tactical and strategic models in which the lot sizing problem is a core substructure, such as integrated production-distribution planning or supplier selection. Recent advances in both directions are discussed. Finally, we give some concluding remarks and point out interesting areas for future research

Self-adaptive randomized constructive heuristics for the multi-item capacitated lot-sizing problem

Capacitated lot-sizing problems (CLSPs) are important and challenging optimization problems in production planning. Amongst the many approaches developed for CLSPs, constructive heuristics are known to be the most intuitive and fastest method for finding good feasible solutions for the CLSPs, and therefore are often used as a subroutine in building more sophisticated exact and metaheuristic approaches. Classical constructive heuristics, such as the period-by-period heuristics and lot elimination heuristics, are first introduced in the 1990s, and thereafter widely used in solving the CLSPs. This paper evaluates the performance of period-by-period and lot elimination heuristics, and improves the heuristics using perturbation techniques and self-adaptive methods. We have also proposed a procedure for automatically adjusting the parameters of the proposed heuristics so that the values of the parameters can be chosen based on features of individual instances. Experimental results show that the proposed self-adaptive randomized period-by-period constructive heuristics are efficient and can find better solutions with less computational time than the tabu search and lot elimination heuristics. When the proposed constructive heuristic is used in a basic tabu search framework, high-quality solutions with 0.88% average optimality gap can be obtained on benchmark instances of 12 periods and 12 items, and optimality gap within 1.2% for the instances with 24 periods and 24 items

Just-In-Time in high variety / low volume manufacturing environments.

Available from British Library Document Supply Centre-DSC:DXN049763 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

Optimal control of production and distribution in a supply chain system operating under a JIT delivery policy

This research deals with a supply chain system where the production or manufacturing facility operates under a just-in-time (JIT) environment, and the facility consists of raw material suppliers, manufacturers, and retailers where inventory of raw materials, work-in-process, and finished goods are involved, respectively. This work considers that the production of finished goods in one cycle starts just after the production or uptime in preceding cycle to minimize the idle time of the facility. Considering this scenario, inventory models are developed for different delivery situations: (a) perfect matching condition where no finished good remains after the shipments and (b) imperfect matching condition where some finished goods remain after the shipments. In this research, the problems are categorized as integer and mixed integer non-linear programming problems which are solved to find optimum number of orders and shipments, optimum production quantity, and minimum system cost. Moreover, multi-supplier and multi-buyer operations, where raw materials are ordered from different suppliers and finished goods are delivered to different customers, are considered. In addition to these problems, a single facility lot-sizing model is applied in perfect and imperfect matching cases, and, multi-supplier and multi-buyer case, to concentrate on more practical supply chain environments. All the problems described in this research are non-convex functions for which the closed form solutions are cumbersome. Therefore, the heuristic solutions are developed to find the optimal lot-sizing techniques. Additionally, the multi-supplier and multi-buyer problem is solved with the help of integer approximation and the divide and conquer rule. The solutions are tested through numerical examples. Furthermore, the sensitivity analyses are performed to observe the variations of the different cost functions. Also, this research proposes an alternate delivery schedule of finished product supply, for which both manufacturers and buyers will be benefited economically. The production and supply chain management play a significant role for the necessary amounts of materials and parts arrive at the proper time and place. With the models obtained in this research, managers can quickly respond to consumers\u27 demand by determining the right policies to order raw materials, to manage their production schedule efficiently and to deliver finished goods just-in-time

Paints supply chain optimisation

Imperial Users onl