M.L. Mittal

A multi-agent system for distributed multi-project scheduling: An auction-based negotiation approach

Simultaneously running multiple projects are quite common in industries. These projects require local (always available to the concerned project) and global (shared among the projects) resources that are available in limited quantity. The limited availability of the global resources coupled with compelling schedule requirements at different projects leads to resource conflicts among projects. Effectively resolving these resource conflicts is a challenging task for practicing managers. This paper proposes a novel distributed multi-agent system using auctions based negotiation (DMAS/ABN) approach for resolving the resource conflicts and allocating multiple different types of shared resources amongst multiple competing projects. The existing multi-agent system (MAS) using auction makes use of exact methods (e.g. dynamic programming relaxation) for solving winner determination problem to resolve resource conflicts and allocation of single unit of only one type of shared resource. Consequently these methods fail to converge for some multi-project instances and unsuitable for real life large problems. In this paper the multi-unit combinatorial auction is proposed and winner determination problem is solved by efficient new heuristic. The proposed approach can solve complex large-sized multi-project instances without any limiting assumptions regarding the number of activities, shared resources or the number of projects. Additionally our approach further allows to random project release-time of projects which arrives dynamically over the planning horizon. The DMAS/ABN is tested on standard set of 140 problem instances. The results obtained are benchmarked against the three state-of-the-art decentralized algorithms and two existing centralized methods. For 82 of 140 instances DMAS/ABN found new best solutions with respect to average project delay (APD) and produced schedules on an average 16.79% (with maximum 57.09%) lower APD than all the five methods for solving the same class of problems.

Traveling Salesman Problem: an Overview of Applications, Formulations, and Solution Approaches

1.1 Origin The traveling salesman problem (TSP) were studied in the 18th century by a mathematician from Ireland named Sir William Rowam Hamilton and by the British mathematician named Thomas Penyngton Kirkman. Detailed discussion about the work of Hamilton & Kirkman can be seen from the book titled Graph Theory (Biggs et al. 1976). It is believed that the general form of the TSP have been first studied by Kalr Menger in Vienna and Harvard. The problem was later promoted by Hassler, Whitney & Merrill at Princeton. A detailed dscription about the connection between Menger & Whitney, and the development of the TSP can be found in (Schrijver, 1960).

Performance measurement in automated manufacturing

Purpose – Todays customer‐focused paradigm of business environment puts tremendous pressures of quality, delivery, dependability, flexibility and cost on the manufacturing organisation. Automatic manufacturing systems offer several advantages and are increasingly being adopted as a strategy to improve the performance of manufacturing organisations. Automatic manufacturing systems are highly sophisticated and expensive, and it is therefore important to maximise their productivity. Yet, one can improve only what one can measure. Performance measurement is the key to improving performance, and is a prerequisite to diagnosing, trouble‐shooting and improving the production system. Accordingly, performance measurement has been attracting increasing attention over the last two decades, and several frameworks have emerged for the design, review, evaluation and improvement of performance measurement systems for businesses and manufacturing organizations. The performance measurement, monitoring and continuous prod...

Improving productivity in Indian SMEs

The manufacturing environment is now so competitive that the companies must not only continuously improve their performance, but also do it faster than others. Small and Medium Enterprises (SMEs) significantly contribute to the industrial output of an economy, and must be competitive for the national economy to be competitive in this era of international business. With almost all productivity improvement (PI) tools requiring a working knowledge of statistics, the Indian SME manager with his semi-literate workforce with little or no technical and mathematical training needs a simple and heuristic PI tool that addresses his particular needs. This article proposes a simple scheduling heuristic to improve productivity quickly and effectively and demonstrates its application and benefits through a case study in a spring manufacturing SME.

Interpretive structural modeling-based framework for mass customisation enablers: an Indian footwear case

Abstract In the epoch of open economy and with the emergence of availability of individualised products over the Internet, Indian manufacturing industries are facing an enormous pressure to become more flexible and responsive, to accomplish customer’s varied and increasing demands. Mass customisation (MC) is about developing a customised product on demand for a particular customer after reception of a real order and producing it with the similar operational efficiency as one would anticipate from a mass-produced product. MC takes into account the merits of both the earlier systems of production, i.e. mass production and craft production. The craft production satisfies the personalised demands of customers and the mass production produces a limited variety of products at lower cost. Industries in developing countries such as India confront pressure from several perspectives to adopt MC. This study has been presented in the context of Indian manufacturing industries, and particularly for footwear industries to examine the enablers of MC. Achieving MC, however, require certain enabling technologies and processes in place. Several such enablers have been identified from the research literature. The objective of this study it to key out significantly important enablers for MC using interpretive structural modelling (ISM), and develop a hierarchy of these enablers for the Indian footwear units. ISM results show that modularity-based practices, digital manufacturing practices and supply chain integration are the most important MC enablers. Enhanced flexibility and responsiveness in the footwear production system can be achieved through modular and reconfigurable production system.

Two-phase heuristics for scheduling of multiple projects

This paper deals with the problem of scheduling of multiple projects sharing a common pool of resources. New two-phase heuristics are proposed and compared with the existing single and two-phase heuristics. These two-phase heuristics are based on a two-stage prioritisation process of activities for resource allocation in which, at any decision point, the projects are first prioritised as per project selection rule and eligible activities in the projects are then prioritised as per activity selection rule. The two-phase heuristics are categorized into look-ahead and non-look-ahead type based on the project selection rules used. Performance of the heuristics is evaluated in two stages for two performance measures – minimising mean project delay and minimising increase over critical project duration. The results show that the some look-ahead heuristics produces better schedules when used with appropriate minimum/maximum criterion. The results also show that the heuristics which are superior in minimising mean project delay generally perform poorly in minimising increase over critical project duration.

Modified simulated annealing based approach for multi objective facility layout problem

In this paper a modified simulated annealing (SA) based approach is presented for solving multi objective facility layout problem (MOFLP). It can incorporate more than two objectives that may be qualitative or quantitative in nature. Computational results show superiority of the proposed modified SA based approach for MOFLP over past approaches available in literature. To validate the proposed SA based approach, it is tested on instances taken from the literature which shows that the proposed approach provides promising results.

A new heuristic approach for solving facility layout problem

This paper proposes a new heuristic approach for solving facility layout problem (FLP) which is traditionally formulated as quadratic assignment problem (QAP). In this paper, FLP is formulated as linear assignment problem (LAP) consisting of facility pair and location pair. Being linear in nature LAP can be solved efficiently. Solution of LAP provides lower bound on corresponding QAP formulation of FLP. Heuristic procedure is applied to solve FLP from sets of LAP solution. Proposed heuristic is tested on benchmark instances taken from literature and compared with other heuristics available in literature. Computational results show that proposed heuristic provides a good quality approximate solution. This solution can be taken as initial solution for any improvement heuristic to get optimal/near optimal solution for FLP.

A multi-agent based approach for dynamic multi-project scheduling

The earlier research in the area of multi-project scheduling is primarily focused on developing efficient priority rules for setting of due dates for new projects, resource allocation to the active projects, and activity scheduling. The priority rule-based heuristics suffer from the drawbacks of providing poor quality schedules and inflexibility. Recently, the artificial intelligence techniques such as multi-agent technology have been applied for scheduling the static multi-project problems. This paper proposes a multi-agent based framework to solve a distributed resource constrained dynamic multi-project scheduling problem. The architecture of the system is developed and the cooperative negotiation framework of various self-managing agents is described.

Scheduling of multiple projects with resource transfers

In organisations, dealing with projects, multiple projects are run simultaneously sharing a common pool of resources. The resources in such a multi-project environment are generally transferred between the projects, consuming significant amounts of both time and cost. In most of the existing models for multi-project planning and scheduling, however, these transfers are implicitly assumed to occur instantaneously with no extra cost. This assumption of instantaneous resource transfers, in most of the practical situations, is not valid and thus may lead to unrealistic schedules. This article is aimed at modelling of these transfers of resources in multi-project scheduling. A generalised model for inter-project resource transfers is presented and an integer linear program is proposed for minimising the penalty/reward for tardy/early projects, and the cost of idleness and transfer of the resources. A heuristic procedure is also developed and computational results are reported.