In today's economy, manufacturing plants must be able to operate efficiently and respond quickly to changes in the product mix and demand. [1] Layout design has a significant impact on manufacturing efficiency. Initially, it was treated as a static decision but due to improvements in technology, it is possible to rearrange the manufacturing facilities in different scenarios. The Plant layout affects on the total cost in the industry. Nowadays DYNAMIC layout is becoming an important issue. DYNAMIC layout is the different layout at different time periods to satisfy the needs of industry, due to change in product, or reduced product life cycle, or change in demand. Layout PROBLEM is a quadratic assignment PROBLEM, and for larger size PROBLEMs it becomes impossible to be solved. So, for solving this PROBLEM Meta heuristic algorithms are used. In this paper, DYNAMIC layout PROBLEM is solved using Genetic algorithm. This DYNAMIC PROBLEM is restricted up to two-time periods only.

Abstract One of the basic assumptions in hub covering PROBLEMs is considering the covering radius as an exogenous parameter which cannot be controlled by the decision maker. Practically and in many real world cases with a negligible increase in costs, to increase the covering radii, it is possible to save the costs of establishing additional hub nodes. Change in PROBLEM parameters during the planning horizon is one of the key factors causing the results of theoretical models to be impractical in real world situations. To dissolve this PROBLEM in this paper a mathematical model for DYNAMIC single allocation hub covering PROBLEM is proposed in which the covering radius of hub nodes is one of the decision variables. Also Due to NP-Hardness of the PROBLEM and huge computational time required to solve the PROBLEM optimally an effective genetic algorithm with DYNAMIC operators is proposed afterwards. Computational results show the satisfying performance of the proposed genetic algorithm in achieving satisfactory results in a reasonable time.

DYNAMIC lot sizing PROBLEM is one of the significant PROBLEMs in industrial units and has been considered by many researchers. Considering the quantity discount in purchasing cost is one of the important and practical aspects of inventory PROBLEMs in the field of inventory control and management, and it has been less focused in terms of stochastic version of DYNAMIC lot-sizing PROBLEM in inventory management. In this paper, the stochastic DYNAMIC lot-sizing PROBLEM with the assumption of existence of all-units quantity discount in purchasing is defined and formulated. Two approaches are presented to handle the solving procedure of this PROBLEM. Since the considered model is a mixed integer non-linear programing model, and the objective function of the model is the only non-linear part of the model. At first, we introduce a piecewise linear approximation model to convert the objective function to a linear term. The main solution approach breaks down the PROBLEM into four levels. At the first level, a branch and bound algorithm branches the PROBLEM on the periods with a predetermined discount level. In this case, the PROBLEM is converted to constrained version of the Sox PROBLEM [10]. This sub PROBLEM raised in each node in the branch and bound algorithm, is a mixed integer non-linear programing too, which is solved based on a DYNAMIC programming approach in the second level. In each stage, in this DYNAMIC programming algorithm, there is a sub-PROBLEM which is solved via a branch and bound algorithm. The PROBLEM raised in each node of the recent branch and bound algorithm is solved with lagrangian relaxation method. The numeric results found in this study indicate that the proposed approach solves the PROBLEM faster than the mathematical programming model using the commercial software GAMS. Moreover, the proposed algorithm for the two discount levels is also compared with the approximate solution in the mentioned software. The results indicate that our algorithm up to 14 periods can not only obtain the exact solution, but also consume less time in contrast to the approximate model.

Hub location PROBLEM is further used in transportation and telecommunication networks (airlines, post delivery services, etc.) so origin-destination pairs, receive or send commodities via special facilities called Hub. Hub median PROBLEM with multiple allocation is an NP-hard PROBLEM which includes both locating hub facilities and allocating non-hub nodes to hubs as minimizes total transportation and location costs. In this paper, the hub median PROBLEM is considered in an environment which network flow varies during the time periods and the capacities of hubs and arcs are unlimited. Also opening and closing hubs in different periods of planning horizon are permitted. The model and the proposed algorithm for this PROBLEM were considered to Iran airlines network using real passenger flows data. Computational results state that the DYNAMIC network compared with static model has lower cost and whatever the number of time periods in DYNAMIC case increases, the cost will be reduced as well.

The PROBLEM of personal identity among others may stem from the following question—what does be the person that you are, from one day to the next, necessarily consist of? The diachronic PROBLEM of personal identity raises question on the necessary and sufficient conditions for the identity of the person over time. The synchronic PROBLEM is grounded in the question of what features or traits characterize a given person at one time. To answer these questions, John Locke discarded the soul and the body as necessary and sufficient substances for personal identity over time. He accepted consciousness as the only criterion for personal identity; the only thing capable of remaining the same and preserving personal identity through change. Though Locke’s argument is somewhat clear and coherent but what remains vague and incoherent is embedded in the question—what exactly is consciousness? How and why should it be the basis or criterion for the determination of personal identity? Using the method of critical analysis, I argue that Locke’s choice of consciousness as the determinant of personal identity, though quite novel, is incoherent and vague. Secondly, Locke had already presumed and anticipated clearly though fallaciously the very thing he wishes to substantiate. I therefore conclude that Locke’s argument is just another way of trying to escape but inadvertently prolonging the difficulty of apparently articulating a distinction between the psychological approach and physiological approach to the PROBLEM of personal identity. However, in my submission, I propose the concept of the “other” as alternative approach— a sort of an extrinsic-intrinsic approach to the PROBLEM of personal identity.

In today's DYNAMIC market, organizations must be adaptive to market fluctuations. In addition, studies show that material-handling cost makes up between 20 and 50 percent of the total operating cost. Therefore, this paper considers the PROBLEM of arranging and rearranging, when there are changes in product mix and demand, manufacturing facilities such that the sum of material handling and rearrangement costs is minimized. This PROBLEM is called the DYNAMIC plant layout PROBLEM (DPLP). In this paper, the authors develop a multi-start simulated annealing for DPLP. To compare the performance of meta-heuristics, data sets taken from literature are used in the comparison.

Many real-world PROBLEMs involve the coordination of multiple agents in DYNAMIC environments. Machines in a factory may need to coordinate the scheduling and execution of jobs to ensure smooth operation as customer demands shift. In the domain of factory operations, adaptive, self-organizing agent-based approaches have been shown to provide very robust solutions. However, these adaptive approaches may require non-trivial amounts of time to respond to large environmental shifts. Techniques exist that have been shown to help many different approaches perform better when PROBLEMs are DYNAMIC. One common technique is the use of information from the past to improve current performance. In many DYNAMIC PROBLEMs, the current state of the environment is often similar to previously seen states. Using information from the past may help to make the system more adaptive to large changes in the environment and to perform better over time. One way to maintain and exploit information from the past is the use of memory, where solutions are stored periodically and can be retrieved and refined when the environment changes. This paper introduces several density-estimation memory systems that are inspired by estimation of distribution for solving one of the hard DYNAMIC PROBLEMs (Factory coordination). In this proposed method, instead of storing only single points in memory, we propose to store clusters of points in each memory entry and to create a model of the points in each cluster. In this proposed method we will be able to store many more points, the computation overhead required for the memory will remain low. The experimental results show the efficiency of the proposed algorithm in comparison with other methods.

Public transportation planning is one of the basic factors in economic and social development modern societies. DIAL-A-RIDE PROBLEM is a topic in the area of public transportation planning which helps to plan a more convenience passenger transportation and also to improve traffic systems. In the DYNAMIC DARP, requests are received throughout the planning horizon and the primary objective is to accept as many requests as possible while satisfying operational constraints. In this research, we developed a two-step algorithm based on DYNAMIC DIAL-A-RIDE PROBLEM. In the first step a new request is accepted, while in the second step the optimum route is found by creating a feasible neighborhood of the current route. The results showed that the proposed algorithm obtains a near optimum solution in a short period of time (in few minutes) with the rate of acceptance above 85 percent of new requests.

A pseudo-DYNAMIC approach solves a multistage transmission expansion planning (MTEP) PROBLEM as a sequence of single stage transmission expansion planning (STEP) PROBLEMs. In this paper, the MTEP PROBLEM is reformulated. Based on the new formulation, a relation is obtained between an MTEP and STEPs local optima. Considering this relation, a new pseudo-DYNAMIC algorithm is proposed. Unlike the ordinary pseudo-DYNAMIC methods, in each stage, it applies a set of high quality local optimums of the STEP PROBLEMs instead of just using the global optimum. The modification improves the search ability of the algorithm. IEEE 24-bus, Colombian 93-bus, Bolivian 57-bus and Iranian 51-bus systems are used to evaluate the proposed and the simulation results have confirmed its effectiveness.