This special issue of the journal Optimization is dedicated to the International Conference on Optimization Modelling and Applications (OPTIMA-2012). OPTIMA-2012 was organized by the Department of Operational Research, University of Delhi, Delhi, India, the Operational Research Society of India, Delhi Chapter, Delhi, India and the Defence Research and Development Organization, New Delhi, India from 29 November 1 December, 2012 at the VPCI Auditorium, University of Delhi, North Campus, Delhi, India. OPTIMA-2012 presented new developments in the theoretical and computational techniques of optimization modelling and related applications in diverse areas. The invited papers submitted to the conference covered a wide range of topics such as optimality and duality, generalized convexity, fuzzy optimization, financial optimization, logistics and supply chain management, evolutionary optimization, machine learning applications, performance evaluation techniques, marketing optimization, hardware and software reliability optimization and optimization applications.
In this special issue of Optimization devoted to OPTIMA-2012, the main focus is on the major theme of the conference, Optimization and Mathematical Modelling with applications in many important real-world decision-making problems. It contains refereed invited papers which were submitted in response to the call for papers for the special issue. The selected papers cover a wide range of optimization models including generalized linear programs, the fixed charge transportation problem, the assignment problem, the quadratic programming problem, the bi-level programming problem, the interval programming problem, the multi-objective programming problem and other mathematical programming problems. In addition, the papers focus on the development of solution methodologies such as network algorithms, heuristics, multi-choice goal programming and regression modelling. The highlights of these papers are briefly summarized below.
The first paper, entitled ‘On the minimization of a class of generalized linear functions on a flow polytope’, by Riccardo Cambini and Claudio Sodini, proposes a solution method for the minimization of a class of generalized linear functions on a flow polytope. The problem is solved by means of a network algorithm, based on graph operations, which lies within the class of the so-called ‘optimal level solutions’ parametric methods.
The second paper, entitled ‘Artificial immune system and sheep flock algorithms for two-stage fixed-charge transportation problem’, by Devika Maridoss, Kannan Govindan and Hamed Soleimani, discusses a two-stage distribution-planning problem of supply chain regarding fixed charges. The focus of the paper is on developing efficient solution methodologies of the selected NP-hard problem.
The third paper, entitled ‘A new software reliability model with Vtub-shaped fault-detection rate and the uncertainty of operating environments’, by Hoang Pham, develops a new software reliability model incorporating the uncertainty of system fault-detection rate per unit of time subject to operating environments.
The fourth paper, entitled ‘A multiobjective optimization framework for optimal selection of supplier portfolio’, by Sy-Ming Guu, Mukesh Mehlawat and Santosh Kumar, proposes a new approach referred to as supplier portfolio optimization, which improves the state of the art of supplier selection by incorporating the benefits of supplier diversification using trade-offs among the criteria of expected unit price, expected score of quality and expected score of delivery.
The fifth paper, entitled ‘Self adaptive artificial bee colony’, by Jagdish Chand Bansal, Harish Sharma, K. V. Arya, Kusum Deep and Millie Pant, develops a self-adaptive artificial bee colony in which good solutions are appointed to exploit the search region in their neighbourhood, while worse solutions to explore the search region. The better solutions are given higher chances to update themselves with the help of a parameter ‘limit’ which changes adaptively.
The sixth paper, entitled ‘Efficient trading frontier: a shortage function approach’, by Reshma Khemchandani and Suresh Chandra, proposes a nonparametric efficiency-based approach for the optimal trading strategy, which trades off the execution risk with the execution cost. A shortage function is defined, which looks for a possible decrease in the execution cost as well as decrease in the execution risk.
The seventh paper, entitled ‘A goal programming approach for a multi-objective multi-choice assignment problem’, by Mukesh Kumar Mehlawat and Santosh Kumar, discusses a multi-objective multi-choice assignment problem considering cost and time objectives subject to some realistic constraints including multi-job assignment. To obtain efficient allocation plans, multi-choice goal programming methodology is used to solve the assignment problem.
The eighth paper, entitled ‘A class of integer linear fractional bilevel programming problems’, by Vikas Sharma, Kalpana Dahiya and Vanita Verma, discusses an integer bilevel programming problem with bounded variables, in which the objective function of the first level is linear fractional, the objective function of the second level is linear and the common constraint region is a polyhedron.
The ninth paper, entitled ‘Optimal multinational project adjustment and selection with random parameters’, by Xiaoxia Huang, Xiaoli Su and Tianyi Zhao, discusses a multi-national project adjustment and selection problem in which project parameters are regarded as random variables. Special cash flows and value sources brought from the new foreign projects and the adjustment of the existing foreign projects are introduced.
The tenth and last paper, entitled ‘A multiobjective portfolio rebalancing model incorporating transaction costs based on incremental discounts’, by Garima Mittal and Mukesh Kumar Mehlawat, proposes a multi-objective model of portfolio rebalancing problem considering return, risk and liquidity as key financial criteria. Further, a more realistic situation of financial market is considered where the portfolio, at the end of a typical time period, will be modified by buying and/or selling asset(s) in response to changing conditions. A real-coded genetic algorithm is developed to solve the portfolio rebalancing problem and build an optimal portfolio.
We sincerely thank all the authors and referees for their efforts in bringing quality publications as per the standards of the journal Optimization.
We would like to express our sincere thanks to the Editor-in-Chief, Professor Christiane Tammer, for granting the special issue of the journal Optimization to the OPTIMA-2012 conference. Professor Tammer has been of great help in giving valuable information from time to time throughout the refereeing process in order to bring quality contributions. We are also extremely thankful to Dr Andreas Löhne, Managing Editor, for his immense help and extremely efficient handling of the manuscripts submitted to our special issue. He has been a great support throughout.
Department of Operational Research, University of Delhi
Delhi, India
Juan-Enrique Martínez-Legaz
Departament d’Economia i d’Història Econòmica
Universitat Autònoma de Barcelona, Bellaterra, Spain