Many optimization problems in various fields have been solved using diverse optimization al gorithms. Traditional optimization techniques such as linear programming (LP), non-linear programming (NL...

A New Heuristic Optimization Algorithm: Harmony Search

The author systematically examines one of the important issues of information — establishing the market price. He introduces the concept of «search» — where a buyer wanting to get a better price, is forced to question sellers. The article deals with various aspects of finding the necessary information.

Economics of Information

We study a single-product setting in which a firm can source from two suppliers, one that is unreliable and another that is reliable but more expensive. Suppliers are capacity constrained, but the reliable supplier may possess volume flexibility. We prove that in the special case in which the reliable supplier has no flexibility and the unreliable supplier has infinite capacity, a risk-neutral firm will pursue a single disruption-management strategy: mitigation by carrying inventory, mitigation by single-sourcing from the reliable supplier, or passive acceptance. We find that a suppliers percentage uptime and the nature of the disruptions (frequent but short versus rare but long) are key determinants of the optimal strategy. For a given percentage uptime, sourcing mitigation is increasingly favored over inventory mitigation as disruptions become less frequent but longer. Further, we show that a mixed mitigation strategy (partial sourcing from the reliable supplier and carrying inventory) can be optimal if the unreliable supplier has finite capacity or if the firm is risk averse.

Contingent rerouting is a possible tactic if the reliable supplier can ramp up its processing capacity, that is, if it has volume flexibility. We find that contingent rerouting is often a component of the optimal disruption-management strategy, and that it can significantly reduce the firms costs. For a given percentage uptime, mitigation rather than contingent rerouting tends to be optimal if disruptions are rare.

https://pubsonline.informs.org/doi/suppl/10.1287/mnsc.1060.0515/suppl_file/mnsc.1060.0515-sm-tomlin_companion_5_06.pdf

On the Value of Mitigation and Contingency Strategies for Managing Supply Chain Disruption Risks

Shuffled Frog Leaping Algorithm (SFLA) is a meta-heuristic for solving discrete optimization problems. Here it is applied to determine optimal discrete pipe sizes for new pipe networks and for network expansions. SFLA is a population based, cooperative search metaphor inspired by natural memetics. The algorithm uses memetic evolution in the form of infection of ideas from one individual to another in a local search. The local search is similar in concept to particle swarm optimization. A shuffling strategy allows for the exchange of information between local searches to move toward a global optimum. This paper summarizes the development of SFLANET, a computer model that links SFLA and the hydraulic simulation software EPANET and its library functions. Application of SFLANET to literature network design problems is then described. Although the algorithm is in its initial stages of development, promising results were obtained.

Optimization of Water Distribution Network Design Using the Shuffled Frog Leaping Algorithm

This paper describes the development of a computer model GANET that involves the application of an area of evolutionary computing, better known as genetic algorithms, to the problem of least-cost design of water distribution networks. Genetic algorithms represent an efficient search method for nonlinear optimization problems; this method is gaining acceptance among water resources managers/planners. These algorithms share the favorable attributes of Monte Carlo techniques over local optimization methods in that they do not require linearizing assumptions nor the calculation of partial derivatives, and they avoid numerical instabilities associated with matrix inversion. In addition, their sampling is global, rather than local, thus reducing the tendency to become entrapped in local minima and avoiding dependency on a starting point. Genetic algorithms are introduced in their original form followed by different improvements that were found to be necessary for their effective implementation in the optimization of water distribution networks. An example taken from the literature illustrates the approach used for the formulation of the problem. To illustrate the capability of GANET to efficiently identify good designs, three previously published problems have been solved. This led to the discovery of inconsistencies in predictions of network performance caused by different interpretations of the widely adopted Hazen-Williams pipe flow equation in the past studies. As well as being very efficient for network optimization, GANET is also easy to use, having almost the same input requirements as hydraulic simulation models. The only additional data requirements are a few genetic algorithm parameters that take values recommended in the literature. Two network examples, one of a new network design and one of parallel network expansion, illustrate the potential of GANET as a tool for water distribution network planning and management.

Genetic Algorithms for Least-Cost Design of Water Distribution Networks

A two-phase decomposition method is proposed for the optimal design of new looped water distribution networks as well as for the parallel expansion of existing ones. The main feature of the method is that it generates a sequence of improving local optimal solutions. The first phase of the method takes a gradient approach with the flow distribution and pumping heads as decision variables and is an extension of the linear programming gradient method proposed by Alperovits and Shamir (1977) for nonlinear modeling. The technique is iterative and produces a local optimal solution. In the second phase the link head losses of this local optimal solution are fixed, and the resulting concave program is solved for the link flows and pumping heads; these then serve to restart the first phase to obtain an improved local optimal solution. The whole procedure continues until no further improvement can be achieved. Some applications and extensions of the method are also discussed.

A two‐phase decomposition method for optimal design of looped water distribution networks

The paper presents a new conceptual model for not-for-profit international development projects that identifies different sets of success criteria and factors in the project life-cycle phases and then provides the dynamic linkages among these criteria and factors. The model can serve as a basis to evaluate the project status and to forecast the results progressively throughout the stages. Thus, it helps the project management team and the key stakeholders prioritize their attention and scarce development resources to ensure successful project completion. Empirical data from a field survey conducted in selected Southeast Asian countries confirm the model's validity and also illustrate important managerial implications.

Success criteria and factors for international development projects: A life‐cycle‐based framework

Time, cost and quality trade-off in project management: a case study

Abstract In 1996, Babu and Suresh proposed a framework to study the trade-off among time, cost and quality using three inter-related linear programming models. This paper describes our attempt to apply the method to an actual cement factory construction project. The purpose is to evaluate the practical applicability of the method by highlighting the managerial insights gained, as well as pointing out key problems and difficulties faced. As consequence, the paper helps practicing project engineers to have realistic expectations of the method. It also provides suggestions to overcome some practical problems if the method is to be applied in real industrial projects.

Time, cost and quality trade-oÄ in project management: a case study

Purpose – The purpose of this study is to investigate the influence of information and communication technology (ICT) adoption on hotel performance in Thailand.Design/methodology/approach – The elements for measuring the level of ICT adoption include: availability of ICT components, integration of ICT components, and intensity of ICT usage. Operational productivity and customer satisfaction were used for measuring hotel performance. To control for the influence of location and employee and management characteristics on hotel productivity, data were collected solely from three star hotels operating in the same location, Phuket, Thailand. Operational productivity was calculated by using data envelopment analysis. A five‐point Likert type scale was employed to measure customer satisfaction. Multiple regression analysis was utilized to assess the relationship between ICT adoption and hotel performance.Findings – The findings indicate that ICT adoption has a significant positive relationship with hotel perform...

Do Ba Khang

Papers

A two‐phase decomposition method for optimal design of looped water distribution networks

Success criteria and factors for international development projects: A life‐cycle‐based framework

Time, cost and quality trade-off in project management: a case study

Time, cost and quality trade-oÄ in project management: a case study

Does ICT adoption enhance hotel performance