Application of Modified Benders Decomposition to Single-Stage Multi-Commodity Multi-Period Warehouse Location Problem: An Empirical Investigation

In the past, researchers have applied Bender’s decomposition to distribution problem and used feasibility constraint to speed up the performance of Bender’s decomposition. Further, the application of Branch and Bound to single-stage multi-commodity single-period warehouse location problem (SSMCSPWLP) with strong constraints has shown that they are more effective. It was also shown in the previous research (in the context of Branch and Bound Methodology) that hybrid formulation for the single-stage single-period multi-commodity warehouse location problem yielded superior results. In this paper we apply Benders’ decomposition to strong and weak formulations of single-stage multi-commodity multi-period warehouse location problem (SSMCMPWLP). As suggested in the previous literature we put feasibility constraints in the pure integer sub- problem to speed up the performance of Benders’ decomposition. We also develop an additional cut (constraint that is again added to pure integer sub-problem) and show that it further speeded up Benders’ Decomposition. This research led to the possibility of applying Benders’ Decomposition to the hybrid formulation of SSMCMPWLP in future.

A Holistic,Proactive and Novel Approach for Pre,During and Post Migration Validation from Subversion to Git

Software development is getting a transition from centralized version control systems(CVCSs)like Subversion to decentralized version control systems(DVCDs)like Git due to lesser efficiency of former in terms of branching,fusion,time,space,merging,offline commits&builds and repository,etc.Git is having a share of 77%of total VCS,followed by Subversion with a share of 13.5%.The majority of software industries are getting a migration from Subversion to Git.Only a few migration tools are available in the software industry.Still,these too lack in many features like lack of identifying the empty directories as premigration check,failover capabilities during migration due to network failure or disk space issue,and detailed report generation as post-migration steps.In this work,a holistic,proactive and novel approach has been presented for pre/during/post-migration validation from Subversion to Git.Many scripts have been developed and executed run-time over various projects for overcoming the limitations of existing migration software tools for a Subversion to Git migration.During premigration,none of the available migration tools has the capability to fetch empty directories of Subversion,which results in an incomplete migration from Subversion to Git.Many Scripts have been developed and executed for pre-migration validation and migration preparation,which overcomes the problem of incomplete migration.Experimentation was conducted in SRLC Software Research Lab,Chicago,USA.During the migration process,in case of loss of network connection or due to any other reason,if migration stops or breaks,available migration tools do not have capabilities to start over from the same point where it left.Various Scripts have been developed and executed to keep the migration revision history in the cache(elastic cache)to start from the same point where it was left due to connection failure.During post-migration,none of the available version control migration tools generate a detailed report giving information about the total size of source Subversion repositories, the total volume of data migrated todestination repositories in Git, total number of pools migrated, time taken formigration, number of Subversion users with email notification, etc. VariousScripts have been developed and executed for the above purpose during thepost-migration process.

ON APPROXIMATE EFFICIENCY FOR NONSMOOTH ROBUST VECTOR OPTIMIZATION PROBLEMS

In this article,we use the robust optimization approach(also called the worst-case approach)for findingε-efficient solutions of the robust multiobjective optimization problem defined as a robust(worst-case)counterpart for the considered nonsmooth multiobjective programming problem with the uncertainty in both the objective and constraint functions.Namely,we establish both necessary and sufficient optimality conditions for a feasible solution to be anε-efficient solution(an approximate efficient solution)of the considered robust multiobjective optimization problem.We also use a scalarizing method in proving these optimality conditions.