Asia-Pacific Journal of Operational Research

Opportunity costs of environmental regulations (OCER) are an important consideration when governments make decisions on the formulation of environmental policies and when plants make decisions in response to environmental policies. Aimed at measuring OCER, the current paper proposes an approach in which the achievements of environmental control implemented by a production unit are considered. We quantify and define the achievements as "desirable" environmental outputs. In this way, for a production unit, producing normal desirable outputs and reaching environmental outputs is a tradeoff. OCER is measured by calculating a maximum amount of increasable normal outputs when production units do not need to produce any environmental outputs. Directional distance functions and data envelopment analysis (DEA) techniques are used to calculate OCER. The approach is applied to an empirical illustration based on Taiwan's port industry covering the period 2001–2007. It is found that the industry incurred opportunity costs due to environmental regulations equivalent to 1.8% of total revenue it creates. However, the OCER are significantly less than the economic losses due to productive inefficiency (PIE).

A medianoid problem is a competitive location problem that determines the locations of a number of new service facilities that are competing with existing facilities for service to customers. This paper studies the medianoid problem on the plane with Manhattan distance. For the medianoid problem with binary customer preferences, i.e., a case where customers choose the closest facility to satisfy their entire demand, we show that the general problem is NP-hard and present solution methods to solve various special cases in polynomial time. We also show that the problem with partially binary customer preferences can be solved with a similar approach we develop for the model with binary customer preferences.

Coordination is imperative for improving supply chain performance. In this paper, we focus on coordination of a two-echelon supply chain consisting of a manufacturer and a price-setting retailer, which operates for a single product. Customer demand is influenced by retailer's instantaneous inventory level and selling price. The integrated system and the decentralized scenario, by considering manufacturer as the Stackelberg leader, are discussed. It is shown that conventional revenue sharing contract cannot coordinate the system but revenue and cost sharing (RCS) contract is able to coordinate the system and leads to a win–win outcome. The key contract parameters — cost sharing fraction, along with revenue sharing fraction and wholesale price are determined under explicit and implicit information of retailer's cost structure. Finally, it is shown that range of cost sharing fraction that leads to win–win situation is independent of the format of cost structure of retailer. Numerical examples are provided to illustrate the development of the model.

We introduce a search game in which a hider has partial information about a searcher's resource. The hider can be a terrorist trying to hide and the searcher can be special forces trying to catch him. The terrorist does not know the number of forces involved in the search but just its distribution. We model this situation by a noncooperative game. In a related setup, which is motivated by wireless networks applications, the terrorist inserts a malicious node in a network, reducing network connectivity and thereby undermining its security. Meanwhile, the network operator applies appropriate measures to detect malicious nodes and maintain network performance. We investigate how the information about the total search resources that are available to the hider can influence the behavior of both players. For the case, where the distribution has two mass points, we prove that the game has a unique equilibrium and moreover, we describe explicitly this equilibrium, its structure and some other properties.

The possibility for more confidential predictions, leaning on scientific methods and accomplishments of information technology leaves more time for the realization of logistic needs. Longstanding ambitions to acquire desired levels of efficiency within the system with minimal costs of resources, materials, energy and money are the features of executive structures of logistic systems. A successful logistic process is based on validation of technological development, indicating the need for a faster and more confidential integration of logistic systems and "instilling confidence" with military units that provide critical support (supply, transport and maintenance) will be reliably realized according to relevance and priority. Conclusions like these impose the necessity that the decision-making process of logistic organs is accessed carefully and systematically, since any wrong decision leads to a reduced state of readiness for military units. To facilitate the day-to-day operation of the Army of Serbia and the completion of both scheduled and unscheduled tasks it is necessary to satisfy the wide range of transport requirements. In this paper, the Adaptive Neuro Fuzzy Inference System (ANFIS) is described, thus making possible a strategy of coordination of transport assets to formulate an automatic control strategy. This model successfully imitates the decision-making process of the chiefs of logistic support. As a result of the research, it is shown that the suggested ANFIS, which has the ability to learn, has a possibility to imitate the decision-making process of the transport support officers and show the level of competence that is comparable with the level of their competence.

We present two new linear algorithms for the single source shortest paths problem. The worst case running time of the first algorithm is O(m + C log C), where m is the number of edges of the input network and C is the ratio of the largest and the smallest edge weight. The pseudo-polynomial character of the time dependence can be overcome by the fact that Dijkstra's kind of shortest paths algorithms can be implemented "from the middle", when the shortest paths to the source are known in advance for a subset of the network vertices. This allows the processing of a subset of the edges with the proposed algorithm and processing of the rest of the edges with any Dijkstra's kind algorithm afterwards. Partial implementation of the algorithm enabled the construction of a second, highly efficient and simple linear algorithm. The proposed algorithm is efficient for all classes of networks and extremely efficient for networks with small C. The decision which classes of networks are most suitable for the proposed approach can be made based on simple parameters. Experimental efficiency analysis shows that this approach significantly reduces total computing time.

This paper considers the single-machine scheduling problem, where job parameters are uncertain and the performance measure is to maximize the weighted number of just-in-time jobs, defined as jobs completed exactly on their due dates. Uncertainty is described through a finite set of well-defined scenarios. The criteria for this environment is to minimize the maximum deviation from optimality for all scenarios. We present the computational complexity results for several cases.

A system of components can be in series, parallel, or combined series/parallel. The components and system are protected individually and overarchingly by a defender, and attacked individually and overarchingly by an attacker. Both layers of protection have to be breached for an attack to be successful. Each component, and the system as a whole, have vulnerabilities determined by individual and overarching protection and attack. The agents choose their effort variables simultaneously and independently to maximize their utilities. Each component and the system have unit costs of protection and attack, and a contest intensity. We show for both the parallel and series systems that the defender always prefers overarching and individual protection and attack, while the attacker always prefers individual protection and attack. Analytical expressions are developed for the agents' effort variables, each individual component's vulnerability, and the system vulnerability. The expenditure ratio, between individual protection and attack, and overarching protection and attack, is shown to increase in the number of components for the parallel system, and decrease in the number of components for the series system. Special cases are considered and interpreted. Comparisons are made with only individual protection and attack. The model is applicable to determine how the defender and attacker should strike the balance between choosing efforts to protect and attack components individually versus overarchingly.