In this article, we propose Simulated Annealing (SA) heuristic to solve Unequal Area Dynamic Facility Layout Problem (FBS) with Flexible Bay Structure (UA-DFLPs with FBS). The UA-DFLP with FBS is the problem of determining the facilities dimension and their location coordinates with flexible bays formation in the layout for various periods of the planning horizon. The UA-DFLP with FBS is more constrained than general UA-DFLP and it is an NP-complete problem. The proposed SA is tested with the available UA-DFLPs instances in the literature. The proposed SA heuristic has given new best solution or the same solution for FBS based problems as compared with the best-known reported in the UA-DFLPs with FBS literature. The proposed SA heuristic is also tested on standard UA-DFLPs used in non-FBS approaches. The SA heuristic solution is not significantly different from the best solution reported in the literature for non-FBS approaches. Equal area DFLP instances are also solved with the proposed SA and the results obtained are promising with the solutions reported in the literature. Hence the results obtained indicate that the proposed SA for UA-DFLP with FBS is effective and versatile for both equal and unequal area dynamic facility layout problems. The computational efficiency of the proposed SA heuristic is very much competitive as compared to other meta-heuristics computational timings reported in the literature.

Customer Demand Information (CDI) sharing plays a vital role in reducing the bullwhip effect as well as in improving the performance of a supply chain. The objective of the present research is to identify the best form of CDI sharing experimentally for a four-stage serial supply chain under lost sales business environment. A supply chain role play game software package is developed for conducting suitable experiments. Different forms of CDI sharing tested in this research are periodic CDI, history of CDI and CDI in the form of distribution. It is found that all forms of CDI sharing have significant impact on the reduction of bullwhip effect compared to non-sharing of information and the upstream stages in the supply chain are benefited the most under CDI sharing. The statistical analysis also confirms that sharing CDI in the form of distribution is the most effective among the various forms of information sharing studied. The percentage reductions in magnitude of order variance under the most benefitted information sharing at distributor and factory stages are 64.43 and 66.04, respectively. It is also found that the performance of a supply chain depends on the degree of customer demand information shared among the stages in the supply chain.

Today Green Supply Chain Management (GSCM) still remains as an attempt alone. For more than a decade, supply chain evolution to be a low carbon chain in an energy and resource constrained world has been posing greater challenges. Though environmental policies remain without much variation towards green operations in an industry, the implantation strategies and stages vary. There have been a number of studies by researchers and a lot of endeavors by organizations to build a green supply chain, mainly because of pressure from the professional bodies like EPA, WEEE, OECD, and Clean Air Act to reduce emissions with growing concerns over climate change issues, global warming, and requirements from policy makers, end users, stake holders and others. But, at the implementation level there lacked a proper framework on GSCM which suggests guidelines for proper planning and coordination, and the practices to be adopted. This indicates the need for a complete strategic approach on the part of decision makers across the supply chain to have sustainability as a corporate social responsibility. The research gap exists in a holistic perception with regard to a product when supply chain stages are mapped for sustainability due to diverse environmental issues. Also, to build a holistic approach, we must know how the stages and levels interact. Thus, in this work, a Parametric Matrix demarking various level and stages of a supply chain related to a product, in general, is developed from various literatures till date. Such a metric will be useful for the industries to identify the bottleneck areas in their supply chain towards sustainability. Hence, the desired and relevant level of factors to be considered at each stage to become green can easily be decided.