Narrow Results

In equitable multiobjective optimization, all of the objectives are uniformly optimized, but in some cases, the decision maker believes that some of them should be uniformly optimized. In order to solve the proposed problem, we introduce the concept of equitable $A_P$-efficiency, where $P=\{P_1,P_2,\dots ,P_n\}$ is a partition of the index set of objective functions and the preference matrix $A_P$ is the direct sum of the matrices $A_1,A_2,\dots ,A_n$, in which $A_k$ is a preference matrix for the objective functions in the class $P_k$ for $k=1,2,\dots ,n$. We examine some theoretical and practical aspects of equitably $A_P$-efficient solutions and provide the some conditions that guarantee the relation of equitable $A_P$-dominance is a $P$-equitable rational preference.

Furthermore, we introduce the new problem with the preference matrix $A_P$ and we decompose it into a collection of smaller subproblems. In continuation, the subproblems are solved by the concept of equitable efficiency. Finally, two models are demonstrated to coordinate equitably efficient solutions of the proposed subproblems.

Herein, we report the synthesis of cobalt-coordinated β-β’ bicyclo[2.2.2]octadiene-fused corrole 1-Co and benzo-fused 2-Co with axial PPh₃ ligands. The structures and properties of 1-Co and 2-Co are fully studied via single-crystal X-ray diffraction, UV-Vis spectroscopy, cyclic voltammograms, and density functional theory calculations. The benzo-fusion of 2-Co leads to a reduced energy gap and distinct coordination, photophysical, and redox properties. Compared to 1-Co, 2-Co exhibits increased bond-length alternation, red-shifted UV-vis absorption bands, and decreased aromaticity. For 2-Co, the axial PPh₃ dissociates during both oxidation and reduction processes, but for 1-Co, the dissociation occurs only during reduction. The theoretical calculations further predict a low-lying open-shell singlet state for 2-Co. This study advances the functionalization strategy of cobalt corroles for a broader range of potential applications.

The purpose of this study was to explore the characteristics of logistics networks that facilitate effective coordination by third-party logistics (3PL) enterprises. Utilizing a comprehensive literature review to bridge the existing research gap, this study meticulously examined the relationships between specific keywords within the SCOPUS database through the use of the VOSviewer tool. This preliminary investigation revealed theoretical deficiencies regarding the operations of 3PL enterprises and the concepts of network and logistic coordination, prompting a detailed empirical analysis of 69 networks where 3PL logistics operators were engaged. This analysis was informed by quantitative data collected from these networks, alongside insights from interviews with experts who assessed the performance of the logistics operators and their clients. The research highlighted particular network attributes, derived from logistic coordination mechanisms, that strongly correlate with the sophisticated use of such mechanisms by operators. One significant limitation of this research was its narrow focus on correlation and the examination of traditional network coordination mechanisms. Nevertheless, the outcomes of this study offer valuable insights for both scholars, aiming to refine the theoretical underpinnings of logistic and network coordination and practitioners within the logistics sector. These findings enhance our comprehension of the dynamics influencing logistic coordination’s effectiveness across diverse settings and elucidate the logistics network characteristics that promote successful collaboration among network members and throughout the supply chain.

We study a game for recognising formal languages, in which two players with imperfect information should coordinate on a common decision, given private input words correlated by a finite graph. The players have a common objective to avoid an inadmissible decision, in spite of the uncertainty induced by the input.

We show that the acceptor model based on consensus games characterises context-sensitive languages. Further, we describe the expressiveness of these games in terms of iterated synchronous transductions and identify a subclass that characterises context-free languages.

Coordination games are important to explain efficient and desirable social behavior. Here we study these games by extensive numerical simulation on networked social structures using an evolutionary approach. We show that local network effects may promote selection of efficient equilibria in both pure and general coordination games and may explain social polarization. These results are put into perspective with respect to known theoretical results. The main insight we obtain is that clustering, and especially community structure in social networks has a positive role in promoting socially efficient outcomes.

We present the design of S-NET, a coordination language and component technology based on stream processing. S-NET achieves a near-complete separation between application code, written in a conventional programming language, and coordination code, written in S-NET itself. S-NET boxes integrate existing sequential code as stream-processing components into streaming networks, whose construction is based on algebraic formulae built out of four network combinators. Subtyping on the level of boxes and networks and a tailor-made inheritance mechanism achieve flexible software reuse.

Manufacturers and suppliers offer temporary reductions (or permanent increases) in the price charged to the resellers for a variety of reasons. The trade promotion may be offered to the reseller at a single point in time or over a finite time-span. In addition, in reselling situations, the end demand tends to be sensitive to selling price. It is commonly found that under such trade promotion (or in stockpiling to an announced price increase), not all the quantity purchased by the reseller at discount may be passed on to the final consumer at a reduced selling price. In fact, previous studies have shown that it is optimal for the reseller to carry forward some of the quantity purchased at discount and sell it later at the regular price. It has been suggested in the literature that by placing a restriction on the reseller's purchase quantity, the supplier can restrict the reseller's forward buy quantity. In this paper, we evaluate this approach. In the rest of the paper, we present alternate schemes which are easy to administer and which insure that the supplier avoids the spike in demand that occurs in the unconstrained problem.

Due to the effects of uncertain factors such as seasonal weather and plant/animal diseases, the output of agricultural production is uncertain given certain agricultural inputs. This paper addresses the issue of coordinating agri-food chain with perishable goods by revenue-sharing (RS) contract when both output and demand are random. Following a RS contract, a supplier decides on agricultural input (e) and deliveries all goods with a price (ω) lower than unit production cost to the retailer while a retailer decides on the retail price (p) and return 1–Φ share (percentage) of its revenue to the supplier. For such a contract, the necessary condition of coordinating the chain is that the expected revenue function is concave. Under the channel coordination, the relationship between RS contract parameters ω and Φ as well as the range of Φ are given. For both output and demand random factor with uniform distribution, the concavity of the expected revenue function is presented. A numerical example illustrates the correctness of our analysis. The results of numerical example show that RS contract is able to coordinate the agri-food chain when the expected revenue function is concave. The results also show that the optimal decisions of p and e are closely related to the demand price elasticity and the range of Φ is widened when the expected output increases.

In this paper, a revenue sharing contract is designed to coordinate a distribution channel where the demand of the product is ramp-type price and effort sensitive. It is shown that traditional revenue sharing contract does not coordinate the system. As an alternative, two new mechanisms are proposed (i) revenue sharing with coordinated effort of the retailer alone and (ii) both revenue and effort sharing contract. In addition, a crucial modification of revenue sharing fraction is also proposed. To enhance the applicability of revenue sharing contract, the contract parameters are determined by using bi-level multi-objective fuzzy goal programming technique where manufacturer sets the wholesale price greater than the marginal cost. Numerical examples are presented to illustrate all the models.

Operational collaboration in a supply chain is important due to the fierce competition among supply chains. However, the collaboration in a supply chain is often hindered by its distribution channel’s lack of funds. It is of significance to alleviate the capital constraint problem of the distribution channel and explore new joint operational and financial collaboration solutions. In this paper, we focus on exploring the optimal solution of operational collaboration in the presence of manufacturer collateral. We consider a supply chain consisting of a well-capitalized manufacturer and a capital-constrained retailer that faces difficulties obtaining credit from the bank. To help the retailer access financing for a purchase order, the manufacturer promises to pay the lender a proportion of the retailer’s loan if the retailer goes bankrupt. We find that when the bank credit with manufacturer collateral is considered as a mix of trade credit and bank credit, the retailer’s financing equilibrium depending on the maximum wholesale price what the manufacturer can set, can be neither trade credit nor bank credit alone, but a combination of them. Moreover, the retailer’s order quantity and the chain’s operational collaboration level will benefit from the manufacturer collateral.

This paper analyzes an infinite horizon, single-product, continuous-time inventory model with supply and demand risks to evaluate the impact of coordinating a production policy between a distributor and a supplier. We consider a wholesale-price contract and a shortage penalty contract as a coordination mechanisms in an inventory replenishment system. The demand process is described by a Brownian motion with drift, and this inventory model can be formulated as an impulse control problem with uncertain replenishment quantities. We show that under some assumptions, there exist optimal ordering and production policies. We also provide some numerical examples to investigate the effect of these coordination mechanisms on the expected costs and the optimal policies. The computational experiments reveal that (i) the production quantity in decentralized case is higher than that in the centralized case, (ii) the centralized approach strategy results in the lower joint total cost as compared with independent decision approaches, and (iii) the shortage penalty contract has a beneficial effect on the total cost to the entire supply chain in decentralized system.

We introduce reference dependence to describe the fairness utility functions of channel members and model a dual-channel supply chain (one manufacturer and one retailer) in three scenarios: only the manufacturer is concerned with fairness, only the retailer is concerned with fairness, and both parties are concerned with fairness. The ordering decisions and coordination of a dual-channel supply chain under the online-to-offline (O2O) business model are studied. Nash equilibrium solutions exist for the channel order quantities in all three scenarios, and the inventory transshipment strategy can be used to coordinate the dual-channel supply chain under the O2O business model. Numerical examples are used to analyze the effectiveness and feasibility of coordination. The inventory transshipment strategy can be used to directly coordinate the dual-channel supply chain when only the manufacturer is concerned with fairness. The retailer feels unfair in the other two scenarios, which affects cooperation. To maintain cooperation with the retailer and achieve optimal supply chain efficiency and channel coordination, the manufacturer must compensate the retailer or choose one with fewer expectations regarding its channel status or fewer fairness concerns.

This paper investigates the coordination problem of a supply chain (SC) composed of a manufacturer and a retailer both exhibiting corporate social responsibility (CSR) under generic random demand. Under a centralized decision, the unimodality of the expected profit is proven, and the expected profit of the SC is shown to be larger than that of the SC without CSR. Under a decentralized decision dominated by the manufacturer, the manufacturer determines the wholesale price and its CSR investment, and then the retailer decides the order quantity and its CSR investment. After showing that the revenue-sharing (RS) contract is not able to coordinate the SC, a modified RS (MRS) contract is proposed to coordinate the SC. At last, the numerical examples in which random demands follow normal distribution and uniform distribution are used to illustrate the validity of the theoretical analysis and the coordination effectiveness of the MRS contract.

Software development processes are highly creative, and therefore prone to change frequently. Also, recent developments show that most software projects require knowledge and skills in a lot of areas. Since the necessary expertise often cannot be found at one development site, the necessity arises to distribute projects among several sites, or form "virtual" corporations, where software development is shared between several companies. The first point makes it necessary to support changes by identifying and notifying the people affected by a change. The second point emphasizes this necessity, while also complicating project planning and management: changes in one development site or company might necessitate replanning in several locations. In this paper, we introduce the MILOS approach, which provides concepts to integrate process modeling, planning, scheduling and enactment in one system. Thus dynamic plan changes, as well as automated feedback from execution to the project plan can be supported.

Firstly, some novel understanding about agents and multi-agent systems, in particular, agentization and coordination, is presented to build a consensus. Afterwards, a brief overview is given of the papers that are included in this special issue.

In this paper we present a process management technology for the coordination of creative and large scale distributed processes. Our approach is the result of usage analysis in domains like Software Development, Architecture/Engineering/Construction, and e-Learning processes. The basic conclusions of these experiments are the following: (1) cooperative processes are described in the same way as production processes, but these descriptions are interpreted in a different way depending on the nature of the process, (2) the interpretation of process description depends mainly on the required flexibility of control flow and of data flow, and on the relationship between them, (3) the management of intermediate results is a central feature for supporting the cooperation inherent to these processes. COO-flow is a process technology that results from these studies. It is based on two complementing contributions: anticipation that allows succeeding activities to cooperate, and COO-transactions that allows parallel activities to cooperate. This paper introduces COO-flow characteristics, gives a (partial) formalization and briefly discusses its Web implementation.

In this paper, we introduce a component coordination model (CCM) that is embedded into the applications during software architecture design. The CCM is driven by the use-context model, which directly reflects the role-based model that abstracts system behaviors as a computational organization comprising various role relationships. It then focuses on exposing the design of software components to be separated from their execution contexts. These separate concerns — computation, coordination, and policies imposed on a given use-context — form the principal concept of our approach. Finally, a case study using the proposed model has been demonstrated in order to provide the feasibility of the introduced approach.

We present modeling strategies that describe the motion and interaction of groups of pedestrians in obscured spaces. We start off with an approach based on balance equations in terms of measures and then we exploit the descriptive power of a probabilistic cellular automaton model.

Based on a variation of the simple symmetric random walk on the square lattice, we test the interplay between population size and an interpersonal attraction parameter for the evacuation of confined and darkened spaces. We argue that information overload and coordination costs associated with information processing in small groups are two key processes that influence the evacuation rate. Our results show that substantial computational resources are necessary to compensate for incomplete information — the more individuals in (information processing) groups the higher the exit rate for low population size. For simple social systems, it is likely that the individual representations are not redundant and large group sizes ensure that this non-redundant information is actually available to a substantial number of individuals. For complex social systems, information redundancy makes information evaluation and transfer inefficient and, as such, group size becomes a drawback rather than a benefit. The effect of group sizes on outgoing fluxes, evacuation times and wall effects is carefully studied with a Monte Carlo framework accounting also for the presence of an internal obstacle.

We show how two novel tools in logic programming for AI (namely, continuation-based linear and timeless assumptions, and Datalog grammars) can assist us in producing terse treatments of difficult language processing phenomena. As a proof of concept, we present a concise parser for Datalog grammars (logic grammars where strings are represented with numbered word boundaries rather than as lists of words) that uses assumptions and a combination of left-corner parsing and charting. We then study two test cases of this parser's application: complete constituent coordination, and error diagnosis and correction.

We consider applications where agents have to cooperate without any communication taking place between them, apart from the fact that they can see part of the environment in which they act. We present a multi-agent system, defined in Golog, that needs to service tasks whose value degrades in time. Initial plans, reflecting prior knowledge about the environment, are expressed as Golog procedures, and are provided to the agents. Then the agents are trained using reinforcement learning, in order to ensure coordination both at the action level and at the plan level. This ensures better scalability and increased performance of the system.