Historically, management theory has ignored the constraints imposed by the biophysical (natural) environment. Building upon resource-based theory, this article attempts to fill this void by proposing a natural-resource-based view of the firm—a theory of competitive advantage based upon the firm's relationship to the natural environment. It is composed of three interconnected strategies: pollution prevention, product stewardship, and sustainable development. Propositions are advanced for each of these strategies regarding key resource requirements and their contributions to sustained competitive advantage.

A natural resource-based view of the firm

An interactive possibilistic programming approach for multiple objective supply chain master planning

FEM prediction of welding residual stress and distortion in carbon steel considering phase transformation effects

Simulation for manufacturing system design and operation: Literature review and analysis

Mathematical programming models for supply chain production and transport planning

Class-based storage policy distributes products among a number of classes and for each class it reserves a region within the storage area. The procedures reported in the literature for formation of storage classes primarily consider order-picking cost ignoring storage-space cost. Moreover, in these procedures items are ordered on the basis of their cube per order index (COI), and items are then partitioned into classes maintaining this ordering. This excludes many possible product combinations in forming classes which may result in inferior solutions. In this paper, a simulated annealing algorithm (SAA) is developed to solve an integer programming model for class formation and storage assignment that considers all possible product combinations, storage-space cost and order-picking cost. Computational experience on randomly generated data sets and an industrial case shows that SAA gives superior results than the benchmark dynamic programming algorithm for class formation with COI ordering restriction.

Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach

A branch and bound algorithm for class based storage location assignment

This paper considers production planning of multi-site production facilities with substitutable capacities serving multiple selling locations where the supplying plant is dynamically determined. A linear programming model is developed to produce the time and capacity aggregated plan and the detailed plan simultaneously to overcome the drawback of the hierarchical planning approaches of not yielding a feasible and/or an optimal lower-level (i.e. detailed) plan. Different time grids and planning horizons for aggregate and detailed planning are appropriately used to reduce the computational burden. Factors such as the limitations of storage space, raw material availability and production capacity at plants and a requirement of maintaining a minimum level of inventory buffer have been modelled. The proposed methodology generated high quality production and dispatch plans when applied to a consumer goods company case.

An integrated aggregate and detailed planning in a multi-site production environment using linear programming

Cell formation (CF) consists of identifying machine groups (MGs) and part families (PFs). Many CF procedures use a part machine matrix as an input and attempt to obtain a block diagonal form. A perfect diagonalization of the part machine matrix to form exclusive PFs and MGs is not possible in many instances. Considering alternate routeings (i.e. alternate plans for the parts and additional copies of machines) improves this diagnonalization. This aspect has not been adequately dealt with in literature. Moreover, existing CF procedures consider indirect measures such as similarity indices, rank order, bond energy etc., that may not obtain a good block diagonalization of the part machine matrix. Also these procedures decouple cell formation and cell evaluation procedures. In this paper a non-linear integer programming model is developed for CF to identify PFs and MGs simultaneously considering alternative routeings. The model combines the evaluation procedure by considering the minimization of a weighted sum...

Cell formation considering alternate routeings

Cell formation is an important problem in the design of a cellular manufacturing system. Despite a large number of papers on cell formation being published, only a handful incorporate operation sequence in intercell move calculations and consider alternative process routings, cell size, production volume and allocating units of identical machines into different cells. Modelling the above factors makes the cell formation problem complex but more realistic. The paper develops a model and solution methodology for a problem of cell formation to minimize the sum of costs of intercell moves, machine investment and machine operating costs considering all the factors mentioned above. An algorithm comprised of simulated annealing and local search heuristics has been developed to solve the model. A limited comparison of the proposed algorithm with an optimal solution generated by complete enumeration of small problems indicates that the algorithm produces a solution of excellent quality. Large problems with 100 par...

https://www.iimahd.ernet.in/assets/upload/faculty/s2.pdf

Gajendra Kumar Adil

Papers

Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach

A branch and bound algorithm for class based storage location assignment

An integrated aggregate and detailed planning in a multi-site production environment using linear programming

Cell formation considering alternate routeings

Efficient algorithm for cell formation with sequence data, machine replications and alternative process routings